2022-01-21T18:20:04Z
http://www.iapress.org/index.php/soic/oai
oai:ojs.localhost:article/6
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"131201 2013 eng "
2310-5070
2311-004X
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Mixture models of geometric distributions in genomic analysis of inter-nucleotide distances
Freitas, Adelaide Valente
University of Aveiro
Afreixo, Vera
University of Aveiro
Cruz, Sara Escudeiro
Agrarian School of Coimbra
The mapping defined by inter-nucleotide distances (InD) provides a reversible numerical representation of the primary structure of DNA. If nucleotides were independently placed along the genome, a finite mixture model of four geometric distributions could be fitted to the InD where the four marginal distributions would be the expected distributions of the four nucleotide types. We analyze a finite mixture model of geometric distributions (f_2), with marginals not explicitly addressed to the nucleotide types, as an approximation to the InD. We use BIC in the composite likelihood framework for choosing the number of components of the mixture and the EM algorithm for estimating the model parameters. Based on divergence profiles, an experimental study was carried out on the complete genomes of 45 species to evaluate f_2. Although the proposed model is not suited to the InD, our analysis shows that divergence profiles involving the empirical distribution of the InD are also exhibited by profiles involving f_2. It suggests that statistical regularities of the InD can be described by the model f_2. Some characteristics of the DNA sequences captured by the model f_2 are illustrated. In particular, clusterings of subgroups of eukaryotes (primates, mammalians, animals and plants) are detected.
International Academic Press
2013-11-11 07:26:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/2013.12.2
Statistics, Optimization & Information Computing; Vol 1 No 1 (2013)
eng
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oai:ojs.localhost:article/8
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"131201 2013 eng "
2310-5070
2311-004X
dc
A primal-dual large-update interior-point algorithm for semi-definite optimization based on a new kernel function
Zhao, Dequan
College of Science, China Three Gorges University
Zhang, Mingwang
College of Science, China Three Gorges University
Based on a new parametric kernel function, this paper presents a primal-dual large-update interior-point algorithm (IPM) for semi-definite optimization (SDO) problems. The new parametric function is neither self-regular function nor the usual logarithmic barrier function. It is strongly convex and possesses some novel analytic properties. We analyse this new parametric kernel function and show that the proposed algorithm has favorable complexity bound in terms of the analytic properties of the kernel function. Moreover, the complexity bound for our large-update IPM is shown to be O(\sqrt{n}(\log n)^2 \log\frac{n}{\epsilon}). Some numerical results are reported to illustrate the feasibility of the proposed algorithm.
International Academic Press
2013-11-11 07:26:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/2013.12.4
Statistics, Optimization & Information Computing; Vol 1 No 1 (2013)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/10
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"131201 2013 eng "
2310-5070
2311-004X
dc
Absence of pure Nash equilibria in a class of co-ordination games
Cannings, Chris
School of Mathematics and Statistics,
University of Sheffield, UK http://chris-cannings.co.uk/
Cannings, Rob
We prove that for a certain class of co-ordination games with increasing payoffs for co-ordination there are not necessarily pure Nash equilibria. This is achieved by introducing a particular model for the payoffs. This result is in contrast to the congestion game with decreasing payoff. We discuss a generalization of the model introduced which is of independent interest.
International Academic Press
2013-11-11 07:26:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/2013.12.1
Statistics, Optimization & Information Computing; Vol 1 No 1 (2013)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/16
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"140824 2014 eng "
2310-5070
2311-004X
dc
A new interpretation of the WZ factorization using block scaled ABS algorithms
Golpar-Raboky, Effat
Mahdavi-Amiri, Nezam
Sharif University of Technology
The WZ factorization suitable for parallel computing, was introduced by Evans. A block generalization of the ABS class of methods for the solution of linear system of equations is given and it is shown that it covers the whole class of conjugate direction methods dened by Stewart. The methods produce a factorization of the coecient matrix implicitly, generating well known matrix factorizations. Here, we show how to set the parameters of a block ABS algorithm to compute the WZ and ZW fac- torizations of a nonsingular matrix as well as the WTW and ZTZ factorizations of a symmetric positives denite matrix. We also show how to appropriate the pa- rameters to construct algorithms for computing the QZ and the QW factorizations, where QTQ is an X-matrix. We also provide a new interpretation of the necessary and sucient condition for the existence of the WZ and the ZW factorizations of a nonsingular matrix.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140906
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/17
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"131201 2013 eng "
2310-5070
2311-004X
dc
Two sample Bayes prediction scenario under right censored repairable system
Prakash, Gyan
Department Of Community Medicine, S. N. Medical College
Kumar, Sarvesh
Department Of Obs. & Gyn., S. N. Medical College
The objective of the present article is to study the behavior of the Bayes predeiction length of interval based on Two-Sample Bayes prediction scenario. A repairable system is considered here with the assumption that repair hazard rate increases monotonically as the time parameter increases. Under the right censoring criterion, the Bayes prediction length of interval and HPD intervals have been obtain here for the underlying model.
International Academic Press
2013-11-11 07:26:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/2013.12.3
Statistics, Optimization & Information Computing; Vol 1 No 1 (2013)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/19
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"140222 2014 eng "
2310-5070
2311-004X
dc
Some Estimation Approaches of Intensities for a Two Stage Open Queueing Network
Pathare, Suresh B
Indira College of Commerce and Science, Pune ,India
Gedam, Vinayak K
Department of Statistics, University of Pune, Pune-41107
In this paper we propose a consistent and asymptotically normal estimator (CAN) for intensity parameters for a queueing network with distribution-free inter-arrival and service times. Using this estimator and its estimated variance, some asymptotic confidence interval of intensities are constructed. Exact- t, Bootstrap-t, Variance-stabilized bootstrap-t, Standard bootstrap, Bayesian bootstrap, Percentile bootstrap and Bias-corrected and accelerated bootstrap are also applied to develop the confidence intervals of intensities. A comparative analysis is conducted to demonstrate performances of the confidence intervals of intensities for a queueing network with short run.
International Academic Press
2014-02-23 23:54:07
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140304
Statistics, Optimization & Information Computing; Vol 2 No 1 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/20
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"131201 2013 eng "
2310-5070
2311-004X
dc
Mean-Variance Portfolio Selection Problem with Stochastic Salary for a Defined Contribution Pension Scheme: A Stochastic Linear-Quadratic-Exponential Framework
Nkeki, Charles
Department of Mathematics,
University of Benin, Nigeria.
This paper examines a mean-variance portfolio selection problem with stochastic salary and inflation protection strategy in the accumulation phase of a defined contribution (DC) pension plan. The utility function is assumed to be quadratic. It was assumed that the flow of contributions made by the PPM are invested into a market that is characterized by a cash account, an inflation-linked bond and a stock. In this paper, inflationlinked bond is traded and used to hedge inflation risks associated with the investment. The aim of this paper is to maximize the expected final wealth and minimize its variance. Efficient frontier for the three classes of assets (under quadratic utility function) that will enable pension plan members (PPMs) to decide their own wealth and risk in their investment profile at retirement was obtained.
International Academic Press
2013-11-11 07:26:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/2013.12.5
Statistics, Optimization & Information Computing; Vol 1 No 1 (2013)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/21
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"140222 2014 eng "
2310-5070
2311-004X
dc
A weighted full-Newton step primal-dual interior point algorithm for convex quadratic optimization
Mohamed, Achache
Mathematics
In this paper a new weighted short-step primal-dual interior point algorithm to solve convex quadratic optimization (CQO) problems. The algorithm uses at each interior iteration afull-Newton step and the strategy of the central to obtain an epsilon-optimal solution of CQO. The algorithm yields the best currently best known theoretical complexity bound namely O(\sqrt(n) log n/epsilon).
International Academic Press
2014-02-23 23:54:07
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140303
Statistics, Optimization & Information Computing; Vol 2 No 1 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/27
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"131128 2013 eng "
2310-5070
2311-004X
dc
Which is better? Regularization in RKHS vs R^m on Reduced SVMs
Zhou, Shuisheng
School of Mathematics and Statistics, Xidian University
In SVMs community, the learning results are always a combination of the selected functions. SVMs have two mainly regularization models to solve the combination coefficients. The most popular model with m input samples is norm-regularized the classification function in a reproducing kernel Hilbert space(RKHS), and it is converted to an optimization problem in R^m by duality or representer theorem. Another important model is generalized support vector machine(GSVM), in which the coefficients of the classification function is norm-regularized in a Euclidean space R^m. In this work, we analyze the difference between them on computing stability, computational complexity and the efficiency of the Newton type algorithms, especially on the reduced SVMs for large scale training problems. Many typical loss functions are considered. Our studies show that the model of GSVM has more advantages than the other model. Some experiments are given to support our analysis.
International Academic Press
2013-11-11 07:26:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/2013.12.6
Statistics, Optimization & Information Computing; Vol 1 No 1 (2013)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/28
2022-01-21T18:20:03Z
soic:ART
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"140222 2014 eng "
2310-5070
2311-004X
dc
Stable families of coalitions for network resource allocation problems
Gurvich, Vladimir
Rutgers University
Schreider, Sergei
RMIT University
A very common question appearing in resource management is: what is the optimal way of behaviour of the agents and distribution of limited resources. Is any form of cooperation more preferable strategy than pure competition? How cooperation can be treated in the game theoretic framework: just as one of a set of Pareto optimal solutions or cooperative game theory is a more promising approach? This research is based on results proving the existence of a non-empty K -core, that is, the set of allocations acceptable for the family K of all feasible coalitions, for the case when this family is a set of subtrees of a tree.
A wide range of real situations in resource management, which include optimal water, gas and electricity allocation problems, can be modeled using this class of games. Thus, the present research is pursuing two goals: 1. optimality and 2. stability.
Firstly, we suggest to players to unify their resources and then we optimize the total payoff using some standard LP technique. The same unification and optimization can be done for any coalition of players, not only for the total one. However, players may object unification of resources. It may happen when a feasible coalition can guarantee a better result for every coalitionist. Here we obtain some stability conditions which ensure that this cannot happen for some family K. Such families were characterized by Boros, Gurvich and Vasin [4] as Berge’s normal hypergraphs. Thus, we obtain a solution which is optimal and stable. From practical point of view, we suggest a distribution of profit that would cause no conflict between players.
International Academic Press
2014-02-23 23:54:07
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140301
Statistics, Optimization & Information Computing; Vol 2 No 1 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/33
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"140222 2014 eng "
2310-5070
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dc
Approximated Function Based Spectral Gradient Algorithm for Sparse Signal Recovery
Wang, Weifeng
College of Mathematics and Information Science, Henan University
Wang, Qiuyu
Numerical algorithms for the l0-norm regularized non-smooth non-convex minimization problems have recently became a topic of great interest within signal processing, compressive sensing, statistics, and machine learning. Nevertheless, the l0-norm makes the problem combinatorial and generally computationally intractable. In this paper, we construct a new surrogate function to approximate l0-norm regularization, and subsequently make the discrete optimization problem continuous and smooth. Then we use the well-known spectral gradient algorithm to solve the resulting smooth optimization problem. Experiments are provided which illustrate this method is very promising.
International Academic Press
2014-02-23 23:54:07
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140302
Statistics, Optimization & Information Computing; Vol 2 No 1 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/36
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"141121 2014 eng "
2310-5070
2311-004X
dc
Estimation of the reliability function for two-parameter exponentiated Rayleigh or Burr type X distribution
Pathak, Anupam
DEPARTMENT OF STATISTICS, UNIVERSITY OF DELHI- 110007
INDIA https://mail.google.com/mail/u/0/?shva=1#inbox
Chaturvedi, Ajit
DEPARTMENT OF STATISTICS, UNIVERSITY OF DELHI- 110007
INDIA
Abstract: Problem Statement: The two-parameter exponentiated Rayleigh distribution has been widely used especially in the modelling of life time event data. It provides a statistical model which has a wide variety of application in many areas and the main advantage is its ability in the context of life time event among other distributions. The uniformly minimum variance unbiased and maximum likelihood estimation methods are the way to estimate the parameters of the distribution. In this study we explore and compare the performance of the uniformly minimum variance unbiased and maximum likelihood estimators of the reliability function R(t)=P(X>t) and P=P(X>Y) for the two-parameter exponentiated Rayleigh distribution. Approach: A new technique of obtaining these parametric functions is introduced in which major role is played by the powers of the parameter(s) and the functional forms of the parametric functions to be estimated are not needed. We explore the performance of these estimators numerically under varying conditions. Through the simulation study a comparison are made on the performance of these estimators with respect to the Biasness, Mean Square Error (MSE), 95% confidence length and corresponding coverage percentage. Conclusion: Based on the results of simulation study the UMVUES of R(t) and ‘P’ for the two-parameter exponentiated Rayleigh distribution found to be superior than MLES of R(t) and ‘P’.
International Academic Press
2014-11-21 09:20:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/20141203
Statistics, Optimization & Information Computing; Vol 2 No 4 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/38
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"141121 2014 eng "
2310-5070
2311-004X
dc
A Fast Algorithm for Using Semi-Parametric Random Effects Model for Analyzing Longitudinal Data
Baghfalaki, Taban
Department of Statistics
Shahid Beheshti University
Tehran, Iran
Ganjali, Mojtaba
Department of Statistics, Faculty of Mathematical Sciences, Shahid Beheshti University, Tehran, Iran
Mixed effects models are frequently used for analyzing longitudinal data. Normality assumption of random effects distrbution is a routine assumption for these models, violation of which leads to model misspecifcation and misleading parameter estimates. We propose a semi-parametric approach using gradient function for random effect estimation. In this approach, we relax the normality assumption for random effects by estimating their distribution over a pre-specifed grid. Unknown parameters of the marginal model are estimated using maximum likelihood methods. Some simulation studies and analyzing of a real data set are performed for illustration of the proposed semi-parametric method.
International Academic Press
2014-11-21 09:20:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/20141205
Statistics, Optimization & Information Computing; Vol 2 No 4 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/40
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"140824 2014 eng "
2310-5070
2311-004X
dc
Fuzzy Economic Order Quantity (FEOQ) Model with Units Lost Due to Deterioration
Pattnaik, Monalisha
UTKAL UNIVERSITY
This model investigates the instantaneous fuzzy economic order quantity model by allocating the percentage of units lost due
to deterioration in an on-hand inventory by framing variable ordering cost. The objective is to maximize the fuzzy net profit so as to determine the order quantity, the cycle length and number of units lost due to deterioration in fuzzy decision space. For any given number of replenishment cycles the existence of a
unique optimal replenishment schedule are proved and mathematical model is developed to find some important characteristics for the concavity of the fuzzy net profit function. Numerical examples are provided to illustrate the results of proposed model which benefit the retailer and this policy is important, especially for wasting of deteriorating items. Finally, sensitivity analyses of the fuzzy optimal solution with respect to the major parameters are also studied.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140907
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/45
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"140601 2014 eng "
2310-5070
2311-004X
dc
On the increase rate of random fields from space $Sub_{\varphi}(\Omega)$ on unbounded domains
Kozachenko, Yuriy
Taras Shevchenko National University of Kyiv
Slyvka-Tylyshchak, Anna
Taras Shevchenko National University of Kyiv
This paper mainly focuses on the estimates for distribution of supremum for the normalized φ-sub-Gaussian random fields defined on the unbounded domain. In particular, we obtain the estimates for distribution of supremum for the normalized solution of the hyperbolic equation of mathematical physics, which will be useful to construct modeless. By using this result, we can approximate the solutions of such equation with given accuracy and reliability in the uniform metric.
International Academic Press
2014-05-22 14:41:37
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140601
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/52
2022-01-21T18:20:03Z
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"140601 2014 eng "
2310-5070
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Improvement of CPU time of Linear Discriminant Function based on MNM criterion by IP
Shinmura, Shuichi
Seikei Univ. http://http://sun.econ.seikei.ac.jp/~shinmura/
Revised IP-OLDF (optimal linear discriminant function by integer programming) is a linear discriminant function to minimize the number of misclassifications (NM) of training samples by integer programming (IP). However, IP requires large computation (CPU) time. In this paper, it is proposed how to reduce CPU time by using linear programming (LP). In the first phase, Revised LP-OLDF is applied to all cases, and all cases are categorized into two groups: those that are classified correctly or those that are not classified by support vectors (SVs). In the second phase, Revised IP-OLDF is applied to the misclassified cases by SVs. This method is called Revised IPLP-OLDF.
In this research, it is evaluated whether NM of Revised IPLP-OLDF is good estimate of the minimum number of misclassifications (MNM) by Revised IP-OLDF. Four kinds of the real data—Iris data, Swiss bank note data, student data, and CPD data—are used as training samples. Four kinds of 20,000 re-sampling cases generated from these data are used as the evaluation samples. There are a total of 149 models of all combinations of independent variables by these data. NMs and CPU times of the 149 models are compared with Revised IPLP-OLDF and Revised IP-OLDF. The following results are obtained:
1) Revised IPLP-OLDF significantly improves CPU time.
2) In the case of training samples, all 149 NMs of Revised IPLP-OLDF are equal to the MNM of Revised IP-OLDF.
3) In the case of evaluation samples, most NMs of Revised IPLP-OLDF are equal to NM of Revised IP-OLDF.
4) Generalization abilities of both discriminant functions are concluded to be high, because the difference between the error rates of training and evaluation samples are almost within 2%.
Therefore, Revised IPLP-OLDF is recommended for the analysis of big data instead of Revised IP-OLDF. Next, Revised IPLP-OLDF is compared with LDF and logistic regression by 100-fold cross validation using 100 re-sampling samples. Means of error rates of Revised IPLP-OLDF are remarkable fewer than those of LDF and logistic regression.
International Academic Press
2014-05-22 14:41:37
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140604
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
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oai:ojs.localhost:article/55
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"140601 2014 eng "
2310-5070
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Recurrence Relations for Moments of Order Statistics from the Lindley Distribution with General Multiply Type-II Censored Sample
Al-Zahrani, Bander
King Abdulaziz University
Ali, M A
King Abdulaziz University
In this paper, we derive the recurrence relations for the moments of function of single and two order statistics from Lindley distribution. We also consider the maximum likelihood estimation (MLE) of the parameter of the distribution based on multiply type-II censoring. However maximum likelihood estimator does not have an explicit form for the involved parameter. In order to compute the MLE of the parameter, Monte Carlo simulation is used. A comparative study is presented between classical MLE and MLE from multiply type-II censored sample.
International Academic Press
2014-05-22 14:41:37
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140606
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/56
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"140824 2014 eng "
2310-5070
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Minimax-robust filtering problem for stochastic sequences with stationary increments and cointegrated sequences
Luz, Maksym
Taras Shevchenko National University of Kyiv
Moklyachuk, Mikhail
Taras Shevchenko National University of Kyiv http://probability.univ.kiev.ua/index.php?page=userinfo&person=mmp&lan=en
The problem of optimal estimation of linear functionals $A {\xi}=$ \quad $\sum_{k=0}^{\infty}a (k)\xi(-k)$ and $A_N{\xi}=\sum_{k=0}^{N}a (k)\xi(-k)$ which depend on the unknown values of a stochastic sequence $\xi(m)$ with stationary $n$th increments from observations of the sequence $\xi(m)+\eta(m)$ at points of time $m=0,-1,-2,\ldots$ is considered in the case where the sequence $\eta(m)$ is stationary and uncorrelated with the sequence $\xi(m)$.
Formulas for calculating the mean-square errors and the spectral characteristics of optimal estimates of the functionals are proposed under condition of spectral certainty, where spectral densities of the sequences $\xi(k)$ and $\eta(k)$ are exactly known. The filtering problem for one class of cointegrated sequences is solved. Minimax (robust) method of estimation is applied in the case where spectral densities of the sequences are not known exactly, but sets of admissible spectral densities are given. Formulas that determine the least favorable spectral densities and minimax spectral characteristics are proposed for some definite sets of admissible densities.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140901
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/58
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"150512 2015 eng "
2310-5070
2311-004X
dc
New MLFQ Scheduling Algorithm for Operating Systems Using Dynamic quantum
Kadry, Seifedine
American University of the middle east, Kuwait
Bagdasaryan, Armen
American University of the middle east, Kuwait
The new design of multilevel feedback queue will depend on usage new technique in computing the quantum to produce (ADQ) Auto Detect Quantum which is relied on the burst of each process has enrolled to the system. By summating the burst time of each process has arrived and dividing it by the number of available processes, we can obtained the dynamic quantum in each level of scheduling. The processes are scheduled and shifted down from queue to other according to their remaining bursts time that should be updated periodically. Every queue has a unique auto detected quantum which is gradually increased or decreased from top level to bottom level queues according to the case of arriving processes. Depending on the results of graphical simulating algorithm on cases study, we can discover that a dynamic quantum is very suitable to accommodate low priority processes that still for a long duration to complete their requests, i.e. avoid the starvation of CPU- bounded processes. Although, it stills compatible with high priority processes (I/O-Bounded) to provide a fair interactivity with them. In comparison to traditional MLFQ the performance of the new scheduling technique is better and practical according to the applied results. Additional, we developed suitable software to simulate the new design and test it on different cases to prove it.
International Academic Press
2015-05-12 12:29:34
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150605
Statistics, Optimization & Information Computing; Vol 3 No 2 (2015)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/64
2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"140824 2014 eng "
2310-5070
2311-004X
dc
A Modified Fletcher-Reeves-Type Method for Nonsmooth Convex Minimization
Li, Qiong
College of Science, China Three Gorges University
Conjugate gradient methods are efficient for smooth optimization problems, while there are rare conjugate gradient based methods for solving a possibly nondifferentiable convex minimization problem. In this paper by making full use of inherent properties of Moreau-Yosida regularization and descent property of modified conjugate gradient method we propose a modified Fletcher-Reeves-type method for nonsmooth convex minimization. It can be applied to solve large-scale nonsmooth convex minimization problem due to lower storage requirement. The algorithm is globally convergent under mild conditions.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140902
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/67
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soic:ART
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"140601 2014 eng "
2310-5070
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Quadratic third-order tensor optimization problem with quadratic constraints
Yang, Lixing
Department of Electrical and Computer Engineering, New Jersey Institute of Technology, USA
Yang, Qingzhi
Nankai University, China
Zhao, Xiaoming
Nankai University, China
Quadratically constrained quadratic programs (QQPs) problems play an important modeling role for many diverse problems. These problems are in general NP hard and numerically intractable. Semidenite programming (SDP) relaxations often provide good approximate solutions to these hard problems. For several special cases of QQP, e.g., convex programs and trust region subproblems, SDP relaxation provides the exact optimal value, i.e., there is a zero duality gap. However, this is not true for the general QQP, or even the QQP with two convex constraints, but a nonconvex objective.
In this paper, we consider a certain QQP where the variable is neither vector nor matrix but a third-order tensor. This problem can be viewed as a generalization of the ordinary QQP with vector or matrix as it's variant. Under some mild conditions, we rst show that SDP relaxation provides exact optimal solutions for the original problem. Then we focus on two classes of homogeneous quadratic tensor programming problems which have no requirements on the constraints number. For one, we provide an easily implemental polynomial time algorithm to approximately solve the problem and discuss the approximation ratio. For the other, we show there is no gap between the SDP relaxation and itself.
International Academic Press
2014-05-22 14:41:37
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http://www.iapress.org/index.php/soic/article/view/20140605
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
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Accuracy of hemoglobin A1c imputation using fasting plasma glucose in diabetes research using electronic health records data
Xu, Stanley
Institute for Health Research
Kaiser Permanente Colorado
Schroeder, Emily B.
Shetterly, Susan
Goodrich, Glenn K.
O’Connor, Patrick J.
Steiner, John F.
Schmittdiel, Julie A.
Desai, Jay
Pathak, Ram D.
Neugebauer, Romain
Butler, Melissa G.
Kirchner, Lester
Raebel, Marsha A.
In studies that use electronic health record data, imputation of important data elements such as Glycated hemoglobin (A1c) has become common. However, few studies have systematically examined the validity of various imputation strategies for missing A1c values. We derived a complete dataset using an incident diabetes population that has no missing values in A1c, fasting and random plasma glucose (FPG and RPG), age, and gender. We then created missing A1c values under two assumptions: missing completely at random (MCAR) and missing at random (MAR). We then imputed A1c values, compared the imputed values to the true A1c values, and used these data to assess the impact of A1c on initiation of antihyperglycemic therapy. Under MCAR, imputation of A1c based on FPG 1) estimated a continuous A1c within ± 1.88% of the true A1c 68.3% of the time; 2) estimated a categorical A1c within ± one category from the true A1c about 50% of the time. Including RPG in imputation slightly improved the precision but did not improve the accuracy. Under MAR, including gender and age in addition to FPG improved the accuracy of imputed continuous A1c but not categorical A1c. Moreover, imputation of up to 33% of missing A1c values did not change the accuracy and precision and did not alter the impact of A1c on initiation of antihyperglycemic therapy. When using A1c values as a predictor variable, a simple imputation algorithm based only on age, sex, and fasting plasma glucose gave acceptable results.
International Academic Press
2014-05-22 14:41:37
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http://www.iapress.org/index.php/soic/article/view/20140602
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
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Exact travelling wave solutions of the symmetric regularized long wave (SRLW) using analytical methods
Manafian Heris, Jalil
Zamanpour, Isa
In this article, we establish exact travelling wave solutions of the symmetric regularized long wave (SRLW) by using analytical methods. The analytical methods are: the tanh-coth method and the sech^2 method which used to construct solitary wave solutions of nonlinear evolution equations. With the help of symbolic computation, we show that aforementioned methods provide a straightforward and powerful mathematical tool for solving nonlinear partial differential equations.
International Academic Press
2014-02-23 23:54:07
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140305
Statistics, Optimization & Information Computing; Vol 2 No 1 (2014)
eng
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Solving Burger's equation by semi-analytical and implicit method
Manafian Heris, Jalil
Zamanpour, Isa
In this work, the modified Laplace Adomian decomposition method (LADM) is applied to solve the Burgers’ equation. In addition, example that illustrate the pertinent features of this method is presented, and the results of the study is discussed. We prove the convergence of LADM applied to the Burgers’ equation. Also, Burgers’ equation has some discontinuous solutions because of effects of viscosity term. These discontinuities raise phenomenon of shock waves. Some explicit and implicit numerical methods have been experimented on Burgers’ equation but these schemes have not been seen proper in this case because of their conditional stability and existence of viscosity term. We consider two types of box schemes and implement on Burgers’ equation to get better results with no artificial wiggles.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140904
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
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Sparse signals estimation for adaptive sampling
Ordin, Andrey
This paper presents an estimation procedure for sparse signals in adaptive setting. We show that when the pure signal is strong enough, the value of loss function is asymptotically the same as for an optimal estimator up to a constant multiplier.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140905
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
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On the Convergence and O(1/N) Complexity of a Class of Nonlinear Proximal Point Algorithms for Monotonic Variational Inequalities
Wu, Jian
School of Mathematics and Computer Sciences, Gannan Normal University, China.
Yu, Gaohang
School of Mathematics and Computer Sciences, Gannan Normal University, China.
This paper presents a class of proximal point algorithms using a nonlinear proximal term for monotonic variational inequality problems. This work extents proximal point algorithms using Bregman distance for minimization problems, and differs with J. Eckstein's approximate iterations in Bregman-function-based proximal algorithms (1998). We study the convergence of the proposed algorithms and obtain a $O(1/N)$ computing complexity/convergence rate of the algorithms. Further more, connections to some existed popular methods were given, which shows that our algorithm can include these methods within a general form.
International Academic Press
2014-05-22 14:41:37
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140603
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
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Numerical solutions of the Kawahara equation by the septic B-spline collocation method
Karakoc, Battal Gazi
Nevsehir University
Zeybek, Halil
Abdullah Gul University, Kayseri, 38039, Turkey
Ak, Turgut
In this article, a numerical solution of the Kawahara equation is presented by septic B-spline collocation method. Applying the Von-Neumann stability analysis, the present method is shown to be unconditionally stable. The accuracy of the proposed method is checked by two test problems. L2 and L1 error norms and conserved quantities are given at selected times. The obtained results are found in good agreement with the some recent results.
International Academic Press
2014-08-24 22:24:55
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140903
Statistics, Optimization & Information Computing; Vol 2 No 3 (2014)
eng
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"140601 2014 eng "
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Supersaturated plans for variable selection in large databases
Parpoula, Christina
National Technical University of Athens
Koukouvinos, Christos
National Technical University of Athens http://www.math.ntua.gr/~ckoukouv/
Simos, Dimitrios
SBA Research
Stylianou, Stella
University of the Aegean
Over the last decades, the collection and storage of data has become massive with the advance of technology and variable selection has become a fundamental tool to large dimensional statistical modelling problems. In this study we implement data mining techniques, metaheuristics and use experimental designs in databases in order to determine the most relevant variables for classification in regression problems in cases where observations and labels of a large database are available. We propose a database-driven scheme for the encryption of specific fields of a database in order to select an optimal supersaturated design consisting of the variables of a large database which have been found to influence significantly the response outcome. The proposed design selection approach is quite promising, since we are able to retrieve an optimal supersaturated plan using a very small percentage of the available runs, a fact that makes the statistical analysis of a large database computationally feasible and affordable.
International Academic Press
2014-05-22 14:41:37
application/pdf
http://www.iapress.org/index.php/soic/article/view/20140607
Statistics, Optimization & Information Computing; Vol 2 No 2 (2014)
eng
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"150828 2015 eng "
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Estimation Approaches of Mean Response Time for a Two Stage Open Queueing Network Model
Gedam, Vinayak K
Department of Statistics, Savitribai Phule Pune University, Pune-411007.
Pathare, Suresh B
Indira College of Commerce and Science, Pune-411033.
In the analysis of queueing network models, the response time plays an important role in studying the various characteristics. In this paper data based recurrence relation is used to compute a sequence of response time. The sample means from those response times, denoted by $\hat {r_1} $ and $ \hat {r_2}$ are used to estimate true mean response time $r_1$ and $r_2$. Further we construct some confidence intervals for mean response time $r_1$ and $r_2$ of a two stage open queueing network model. A numerical simulation study is conducted in order to demonstrate performance of the proposed estimator $ \hat {r_1} $ and $ \hat {r_2}$ and bootstrap confidence intervals of $ r_1$ and $r_2$. Also we investigate the accuracy of the different confidence intervals by calculating the coverage percentage, average length, relative coverage and relative average length.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150905
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
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"141121 2014 eng "
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Stochastic Funding of a Defined Contribution Pension Plan with Proportional Administrative Costs and Taxation under Mean-Variance Optimization Approach
Nkeki, Charles I
Department of Mathematics,
University of Benin, Nigeria.
This paper aim at studying a mean-variance portfolio selection problem with stochastic salary, proportional administrative costs and taxation in the accumulation phase of a defined contribution (DC) pension scheme. The fund process is subjected to taxation while the contribution of the pension plan member (PPM) is tax exempt. It is assumed that the flow of contributions of a PPM are invested into a market that is characterized by a cash account and a stock. The optimal portfolio processes and expected wealth for the PPM are established. The efficient and parabolic frontiers of a PPM portfolios in mean-variance are obtained. It was found that capital market line can be attained when initial fund and the contribution rate are zero. It was also found that the optimal portfolio process involved an inter-temporal hedging term that will offset any shocks to the stochastic salary of the PPM.
International Academic Press
2014-11-21 09:20:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/20141204
Statistics, Optimization & Information Computing; Vol 2 No 4 (2014)
eng
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"141121 2014 eng "
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Efficient Binary Linear Programming Formulations for Boolean Functions
Gurski, Frank
University of Duesseldorf http://www.cs.hhu.de/en/research-groups/algorithmics-for-hard-problems.html
A very useful tool when designing linear programs for optimization problems is the formulation of logical operations by linear programming constraints. We give efficient linear programming formulation of important n-ary boolean functions f(x_1,\ldots,x_n)=x_{n+1} such as conjunction, disjunction, equivalence, and implication using n+1 boolean variables x1,...,x_{n+1}. For the case that the value f(x1, ...,xn) is not needed for further computations, we even give more compact formulation. Our formulations show that every binary boolean function f(x1,x2)=x3 can be realized by the only three boolean variables x1,x2,x3 and at most four linear programming constraints.
International Academic Press
2014-11-21 09:20:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/20141201
Statistics, Optimization & Information Computing; Vol 2 No 4 (2014)
eng
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"150221 2015 eng "
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A hybrid bird mating optimizer algorithm with teaching-learning-based optimization for global numerical optimization
Zhang, Qingyang
Research Institute of Information and System Computation
Science, Beifang University of Nationalities, China
Yu, Guolin
Research Institute of Information and System Computation
Science, Beifang University of Nationalities, China
Song, Hui
Research Institute of Information and System Computation
Science, Beifang University of Nationalities, China
Bird Mating Optimizer (BMO) is a novel meta-heuristic optimization algorithm inspired by intelligent mating behavior of birds. However, it is still insufficient in convergence of speed and quality of solution. To overcome these drawbacks, this paper proposes a hybrid algorithm (TLBMO), which is established by combining the advantages of Teaching-learning-based optimization (TLBO) and Bird Mating Optimizer (BMO). The performance of TLBMO is evaluated on 23 benchmark functions, and compared with seven state-of-the-art approaches, namely BMO, TLBO, Artificial Bee Bolony (ABC), Particle Swarm Optimization (PSO), Fast Evolution Programming (FEP), Differential Evolution (DE), Group Search Optimization (GSO). Experimental results indicate that the proposed method performs better than other existing algorithms for global numerical optimization.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150305
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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"150221 2015 eng "
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An extended compound gamma model and application to composite fading channels
T, Princy
Centre for Mathematical Sciences, Arunapuram, Kerala, India
Wireless communication systems are subject to short and long-term fading channels. In this paper, an extended form of a statistical model for the composite fading channels is derived from the maximum entropy principle. Subsequently, the composite fading channel is derived by replacing the conditional density by entropy-maximizing distribution (Mathai's pathway model). This pathway model is versatile enough to represent short-term fading as well as the shadowing. The new wireless channel model generalizes the commonly used models for multipath fading and shadowing. In particular, using the G-function, we derive the density function, distribution function and moments of the new model in closed form. These derived results are a suitable device to analyze the performance of composite fading systems such as density function of the Signal Noise to Ratio (SNR), Amount of Fading (AF), and Outage Probability (OP) etc. The results will be shown graphically for different signal and fading parameter values.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150304
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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"141121 2014 eng "
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Multiobjective Fractional Programming Problems and Second Order Generalized Hybrid Invexity Frameworks
Verma, Ram
Texas State University
In this paper, first generalized sufficient efficiency conditions for multiobjective fractional programming based on the generalized hybrid invexities are developed , and then efficient solutions to multiobjective fractional programming problems are established. The obtained results generalize and unify a wide range of investigations in the literature.
International Academic Press
2014-11-21 09:20:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/20141202
Statistics, Optimization & Information Computing; Vol 2 No 4 (2014)
eng
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"150512 2015 eng "
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Parameter Estimation in Multivariate Gamma Distribution
Vaidyanathan, V S
Pondicherry University
Puducherry, India
Vani Lakshmi, R
Pondicherry University, India
Multivariate gamma distribution finds abundant applications in stochastic modelling, hydrology and reliability. Parameter estimation in this distribution is a challenging one as it involves many parameters to be estimated simultaneously. In this paper, the form of multivariate gamma distribution proposed by Mathai and Moschopoulos [10] is considered. This form has nice properties in terms of marginal and conditional densities. A new method of estimation based on optimal search is proposed for estimating the parameters using the marginal distributions and the concepts of maximum likelihood, spacings and least squares. The proposed methodology is easy to implement and is free from calculus. It optimizes the objective function by searching over a wide range of values and determines the estimate of the parameters. The consistency of the estimates is demonstrated in terms of mean, standard deviation and mean square error through simulation studies for different choices of parameters.
International Academic Press
2015-05-12 12:29:34
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150603
Statistics, Optimization & Information Computing; Vol 3 No 2 (2015)
eng
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"150828 2015 eng "
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A new non-monotone filter trust region algorithm for solving nonlinear systems of equalities and inequalities
Gu, Chao
School of Math. and Info., Shanghai
LiXin University of Commerce, P.R.China
Wang, Hua
School of Math. and Info., Shanghai
LiXin University of Commerce, P.R.China
In this paper, we combine filter and non-monotone trust region algorithm for nonlinear systems of equalities and inequalities. The systems of equalities and inequalities are transformed into a continuous equality constrained optimization solved by the new algorithm. Filter method guarantees global convergence of the algorithm under appropriate assumptions. The second order correction step is used to overcome Maratos effect so that superlinearly local convergence is achieved. Preliminary numerical results are reported.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150903
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
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"150221 2015 eng "
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Minimax Interpolation Problem for Random Processes with Stationary Increments
Luz, Maxim
Taras Shevchenko National University of Kyiv
Moklyachuk, Mikhail
Taras Shevchenko National University of Kyiv http://probability.univ.kiev.ua/index.php?page=userinfo&person=mmp&lan=en
The problem of mean-square optimal estimation of the linear functional A_T ξ=\int_{0}^Ta(t) ξ(t)dt that depends on the unknown values of a continuous time random process ξ(t),t ∈ R, with stationary nth increments from observations of the process ξ(t) at time points t ∈ R \ [0;T] is investigated under the condition of spectral certainty as well as under the condition of spectral uncertainty. Formulas for calculation the value of the mean-square error and spectral characteristic of the optimal linear estimate of the functional are derived under the condition of spectral certainty where spectral density oft he process is exactly known. In the case of spectral uncertainty where spectral density of the process is not exactly known, but a class of admissible spectral densities is given, relations that determine the least favourable spectral density and the minimax spectral characteristic are specified.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150303
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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Inexact Accelerated Proximal Gradient Algorithms For Matrix l_{2,1}-Norm Minimization Problem in Multi-Task Feature Learning
Hu, Yaping
East China University of Science and Technology
Wei, Zengxin
Guangxi University
Yuan, Gonglin
Guangxi University
In this paper, we extend the APG method to solve matrix l_{2,1}-norm minimization problem in multi-task feature learning. We investigate that the resulting inner subproblem has closed-form solution which can be easily determined by taking the problem's favorable structures. Under suitable conditions, we can establish a comprehensive convergence result for the proposed method. Furthermore, we present three different inexact APG algorithms by using the Lipschitz constant, the eigenvalue of Hessian matrix and the Barzilai and Borwein parameter in the inexact model, respectively. Numerical experiments on simulated data and real data set are reported to show the efficiency of proposed method.
International Academic Press
2014-11-21 09:20:00
application/pdf
http://www.iapress.org/index.php/soic/article/view/20141206
Statistics, Optimization & Information Computing; Vol 2 No 4 (2014)
eng
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On the GLR and UMP tests in the family with support dependent on the parameter
Eftekharian, Abbas
Hormozgan University
Taheri, S. Mahmoud
University of Tehran
Some general results about the GLR tests, for testing simple hypothesis versus two-sided hypothesis, in the family with support dependent on the parameter, are obtained. In addition, we show that such GLR tests are equivalent to the UMP tests in the same problems. Moreover, we derive the general form of the UMP tests for testing an interval hypothesis versus two-sided alternative.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150902
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
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"150221 2015 eng "
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The 95% confidence intervals of error rates and discriminant coefficients
Shinmura, Shuichi
Seikei University, Japan http://sun.econ.seikei.ac.jp/~shinmura/
Fisher proposed a linear discriminant function (Fisher’s LDF). From 1971, we analysed electrocardiogram (ECG) data in order to develop the diagnostic logic between normal and abnormal symptoms by Fisher’s LDF and a quadratic discriminant function (QDF). Our four years research was inferior to the decision tree logic developed by the medical doctor. After this experience, we discriminated many data and found four problems of the discriminant analysis. A revised Optimal LDF by Integer Programming (Revised IP-OLDF) based on the minimum number of misclassification (minimum NM) criterion resolves three problems entirely [13, 18]. In this research, we discuss fourth problem of the discriminant analysis. There are no standard errors (SEs) of the error rate and discriminant coefficient. We propose a k-fold crossvalidation method. This method offers a model selection technique and a 95% confidence intervals (C.I.) of error rates and discriminant coefficients.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150306
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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"150221 2015 eng "
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Polynomial Chaos based on the parallelized ensemble Kalman filter to estimate precipitation states
Sanchez, Luis
universidad de carabobo
Infante, Saba
Marcano, Jose
Griffin, Victor
This article develops a methodology combining methods of numerical analysis and stochastic differential equations with computational algorithms to treat problems which have complex nonlinear dynamics in high dimensions. A method to estimate parameters and states of a dynamic system is proposed inspired by the parallelized ensemble Kalman filter (PEnKF) and the polynomial chaos theory of Wiener-Askey. The main advantage of the proposal is in providing a precise efficient algorithm with low computational cost. For the analysed data, the methods provide good predictions, spatially and temporally, for the unknown precipitation states for the first 24 hours. Two goodness of fit measures provide confidence in the quality of the model predictions. The performance of the parallel algorithm, measured by the acceleration and efficiency factors, shows an increase of 7% in speed with respect to the sequential version and is most efficient for P = 2 threads.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150307
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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"150221 2015 eng "
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Image reconstruction from incomplete convolution data via total variation regularization
Shen, Zhida
Geng, Zhe
Yang, Junfeng
Department of Mathematics, Nanjing University, China http://math.nju.edu.cn/~jfyang/
Variational models with Total Variation (TV) regularization have long been known to preserve image edges and produce high quality reconstruction. On the other hand, recent theory on compressive sensing has shown that it is feasible to accurately reconstruct images from a few linear measurements via TV regularization. However, in general TV models are difficult to solve due to the nondifferentiability and the universal coupling of variables. In this paper, we propose the use of alternating direction method for image reconstruction from highly incomplete convolution data, where an image is reconstructed as a minimizer of an energy function that sums a TV term for image regularity and a least squares term for data fitting. Our algorithm, called RecPK, takes advantage of problem structures and has an extremely low per-iteration cost. To demonstrate the efficiency of RecPK, we compare it with TwIST, a state-of-the-art algorithm for minimizing TV models. Moreover, we also demonstrate the usefulness of RecPK in image zooming.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150301
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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Adaptive Proximal Point Algorithms for Total Variation Image Restoration
Chen, Ying
School of Mathematics and
Computer Sciences, Gannan Normal University, China
Wu, Jian
College of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, Guangdong province, China
Yu, Gaohang
School of Mathematics and
Computer Sciences, Gannan Normal University, China
Image restoration is a fundamental problem in various areas of imaging sciences. This paper presents a class of adaptive proximal point algorithms (APPA) with contraction strategy for total variational image restoration. In each iteration, the proposed methods choose an adaptive proximal parameter matrix which is not necessary symmetric. In fact, there is an inner extrapolation in the prediction step, which is followed by a correction step for contraction. And the inner extrapolation is implemented by an adaptive scheme. By using the framework of contraction method, global convergence result and a convergence rate of O(1/N) could be established for the proposed methods. Numerical results are reported to illustrate the efficiency of the APPA methods for solving total variation image restoration problems. Comparisons with the state-of-the-art algorithms demonstrate that the proposed methods are comparable and promising.
International Academic Press
2015-02-21 16:59:57
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150302
Statistics, Optimization & Information Computing; Vol 3 No 1 (2015)
eng
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A note on the inertial proximal point method
Mu, Zhenguo
School of Mathematical Sciences, Nanjing Normal University, Nanjing, China
Peng, Yang
Department of Mathematics, Nanjing University, China.
The proximal point method (PPM) for solving maximal monotone operator inclusion problem is a highly powerful tool for algorithm design, analysis and interpretation. To accelerate convergence of the PPM, inertial PPM (iPPM) was proposed in the literature. In this note, we point out that some of the attractive properties of the PPM, e.g., the generated sequence is contractive with the set of solutions, do not hold anymore for iPPM. To partially inherit the advantages of the PPM and meanwhile incorporate inertial extrapolation steps, we propose an iPPM with alternating inertial steps. Our analyses show that the even subsequence generated by the proposed iPPM is contractive with the set of solutions. Moreover, we establish global convergence result under much relaxed conditions on the inertial extrapolation stepsizes, e.g., monotonicity is no longer needed and the stepsizes are significantly enlarged compared to existing methods. Furthermore, we establish certain $o(1/k)$ convergence rate results, where $k$ denotes the iteration counter. These features are new to inertial type PPMs.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150904
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
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"151128 2015 eng "
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Construction of exact solutions to the modified forms of DP and CH equations by analytical methods
Manafian Heris, Jalil
Shahabi, Reza
Asadpour, Mohammad
Faculty of engineering, Marand of University
Zamanpour, Isa
Karaj Branch, Islamic Azad university
Jalali, Jalal
Ahar Branch, Islamic Azad university
In this work, we establish the exact solutions to the modified forms of Degasperis–Procesi (DP) and Camassa–Holm (CH) equations. The generalized (G’/G)-expansion and generalized tanh-coth methods were used to construct solitary wave solutions of nonlinear evolution equations. The generalized (G’/G)-expansion method presents a wider applicability for handling nonlinear wave equations. It is shown that the (G’/G)-expansion method, with the help of symbolic computation, provides a straightforward and powerful mathematical tool for solving nonlinear evolution equations in mathematical physics.
International Academic Press
2015-11-28 19:49:27
application/pdf
http://www.iapress.org/index.php/soic/article/view/20151203
Statistics, Optimization & Information Computing; Vol 3 No 4 (2015)
eng
##submission.copyrightStatement##
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"150512 2015 eng "
2310-5070
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Minimax-robust prediction problem for stochastic sequences with stationary increments and cointegrated sequences
Luz, Maksym
Taras Shevchenko National University of Kyiv
Moklyachuk, Mikhail
Taras Shevchenko National University of Kyiv http://probability.univ.kiev.ua/index.php?page=userinfo&person=mmp&lan=en
The problem of optimal estimation of the linear functionals $A {\xi}=\sum_{k=0}^{\infty}a (k)\xi(k)$ and $A_N{\xi}=\sum_{k=0}^{N}a (k)\xi(k)$ which depend on the unknown values of a stochastic sequence $\xi(m)$ with stationary $n$th increments is considered. Estimates are obtained which are based on observations of the sequence $\xi(m)+\eta(m)$ at points of time $m=-1,-2,\ldots$, where the sequence $\eta(m)$ is stationary and uncorrelated with the sequence $\xi(m)$. Formulas for calculating the mean-square errors and spectral characteristics of the optimal estimates of the functionals are derived in the case of spectral certainty, where spectral densities of the sequences $\xi(m)$ and $\eta(m)$ are exactly known. These results are applied for solving extrapolation problem for cointegrated sequences. In the case where spectral densities of the sequences are not known exactly, but sets of admissible spectral densities are given, the minimax-robust method of estimation is applied. Formulas that determine the least favorable spectral densities and minimax spectral characteristics are proposed for some special classes of admissible densities.
International Academic Press
2015-05-12 12:29:34
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150604
Statistics, Optimization & Information Computing; Vol 3 No 2 (2015)
eng
##submission.copyrightStatement##
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"150512 2015 eng "
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Two new bivariate zero-inflated generalized Poisson distributions with a flexible correlation structure
Zhang, Chi
the University of Hong Kong
Tian, Guoliang
the University of Hong Kong
Huang, Xifen
the University of Hong Kong
To model correlated bivariate count data with extra zero observations, this paper proposes two new bivariate zero-inflated generalized Poisson (ZIGP) distributions by incorporating a multiplicative factor (or dependency parameter) λ, named as Type I and Type II bivariate ZIGP distributions, respectively. The proposed distributions possess a flexible correlation structure and can be used to fit either positively or negatively correlated and either over- or under-dispersed count data, comparing to the existing models that can only fit positively correlated count data with over-dispersion. The two marginal distributions of Type I bivariate ZIGP share a common parameter of zero inflation while the two marginal distributions of Type II bivariate ZIGP have their own parameters of zero inflation, resulting in a much wider range of applications. The important distributional properties are explored and some useful statistical inference methods including maximum likelihood estimations of parameters, standard errors estimation, bootstrap confidence intervals and related testing hypotheses are developed for the two distributions. A real data are thoroughly analyzed by using the proposed distributions and statistical methods. Several simulation studies are conducted to evaluate the performance of the proposed methods.
International Academic Press
2015-05-12 12:29:34
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150601
Statistics, Optimization & Information Computing; Vol 3 No 2 (2015)
eng
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"150512 2015 eng "
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Solve thermal explosion model by central difference and Newton iteration method
Wang, Xijian
Wuyi University
Zeng, Tonghua
Wuyi University
In this paper, the general equation form of a thermal explosion in a vessel with boundary values is firstly presented, later the central difference method and Newton iteration method are used to solve the relevant partial differential equations in one-dimensional and two-dimensional forms, finally the order of convergence of the numerical scheme is verified by numerical experiments and the experiment results are provided.
International Academic Press
2015-05-12 12:29:34
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150606
Statistics, Optimization & Information Computing; Vol 3 No 2 (2015)
eng
##submission.copyrightStatement##
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"150512 2015 eng "
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A Central Limit Theorem for the Volumes of High Excursions of Stationary Associated Random Fields
Demichev, Vadim
Lomonosov Moscow State University, 119991 Moscow, Russia;
The University of Sheffield, S10 2TN Sheffield, UK
Olszewski, Judith Sarah
Institute of Stochastics, Ulm University
We prove that under certain conditions the excursion sets volumes of stationary positively associated random fields converge after rescaling to the normal distribution as the excursion level and the size of the observation window grow. In addition, we provide a number of examples.
International Academic Press
2015-05-12 12:29:34
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150602
Statistics, Optimization & Information Computing; Vol 3 No 2 (2015)
eng
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"150828 2015 eng "
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Mathematical Programming Based on Sufficient Optimality Conditions and Higher Order Exponential Type Generalized Invexities
Verma, Ram
Texas State University
First, a class of comprehensive higher order exponential type generalized $B$-($b,$ $\rho,$ $\eta,$ $\omega,$ $\theta,$ $\tilde{p},$ $\tilde{r},$ $\tilde{s}$)-invexities is introduced, which encompasses most of the existing generalized invexity concepts in the literature, including the Antczak type first order $B$-($b,$ $\eta,$ $\tilde{p},$ $\tilde{r}$)-invexities as well as the Zalmai type $(\alpha,$ $\beta,$ $\gamma,$ $\eta,$ $\rho,$ $\theta$)-invexities, and then a wide range of parametrically sufficient optimality conditions leading to the solvability for discrete minimax fractional programming problems are established with some other related results. To the best of our knowledge, the obtained results are new and general in nature relating the investigations on generalized higher order exponential type invexities.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150907
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
##submission.copyrightStatement##
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"160228 2016 eng "
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Accurate, Fast and Noiseless Image Binarization
Al-Khawand, Wassim
University of Genoa - UNIGE, Italy
Kadry, Seifedine
American University of the middle east, Kuwait
Bozzo, Riccardo
Smaili, Khaled
In this paper, we present an accurate, swift and noiseless image binarization technique that was tested on real life back side container images. Our approach consists of transferring a colored image into grayscale, then to construct the histogram which will be divided into group of colors and after that, the foreground -that can be darker or lighter than the background- will be automatically identified and finally, the foreground boundaries will be assiduously enhanced before creating the binarized image. The average processing time of our proposed method is less than 8 milliseconds which makes it highly suitable for real life multi-user applications.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160304
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
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"151128 2015 eng "
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A novel approach in Multi-hop networks technology with the ratio distribution of two Hyper-Erlang random variables
Kadri, Therrar
Department of Mathematics, Faculty of Sciences, Lebanese International University, Al-Khyara, Lebanon.
Smaili, Khaled
Department of Applied Mathematics, Faculty of Sciences, Lebanese University, Zahle, Lebanon.
Kadry, Seifedine
American University of the middle east, Kuwait
The distribution of ratio of two random variables has been studied by several authors especially when the two random variables are independent and come from the same family. In this paper, the exact distribution of the ratio of two independent Hyper-Erlang distribution is derived. However, closed expressions of the probability density, cumulative distribution function, reliability function, hazard function, moment generating function and the rth moment are found for this ratio distribution and proved to be a linear combination of the Generalized-F distribution. Finally, we will apply our results to real life application in analyzing the performance of wireless communication systems.
International Academic Press
2015-11-28 19:49:27
application/pdf
http://www.iapress.org/index.php/soic/article/view/20151201
Statistics, Optimization & Information Computing; Vol 3 No 4 (2015)
eng
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oai:ojs.localhost:article/144
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"150828 2015 eng "
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Multiobjective approach to optimal control for a dengue transmission model
Denysiuk, Roman
Rodrigues, Helena Sofia
Monteiro, M. Teresa T.
Costa, Lino
Espírito Santo, Isabel
Torres, Delfim F. M.
University of Aveiro http://orcid.org/0000-0001-8641-2505
During the last decades, the global prevalence of dengue progressed dramatically. It is a disease which is now endemic in more than one hundred countries of Africa, America, Asia and the Western Pacific. This study addresses a mathematical model for the dengue disease transmission and finding the most effective ways of controlling the disease. The model is described by a system of ordinary differential equations representing human and vector dynamics. Multiobjective optimization is applied to find the optimal control strategies, considering the simultaneous minimization of infected humans and costs due to insecticide application. The obtained results show that multiobjective optimization is an effective tool for finding the optimal control. The set of trade-off solutions encompasses a whole range of optimal scenarios, providing valuable information about the dynamics of infection transmissions. The results are discussed for different values of model parameters.During the last decades, the global prevalence of dengue progressed dramatically.It is a disease which is now endemic in more than one hundred countries of Africa,America, Asia and the Western Pacific. This study addresses a mathematical modelfor the dengue disease transmission and finding the most effective waysof controlling the disease. The model is described by a system of ordinarydifferential equations representing human and vector dynamics. Multiobjectiveoptimization is applied to find the optimal control strategies, consideringthe simultaneous minimization of infected humans and costs due to insecticide application.The obtained results show that multiobjective optimization is an effective toolfor finding the optimal control. The set of trade-off solutions encompassesa whole range of optimal scenarios, providing valuable information about thedynamics of infection transmissions. The results are discussed for differentvalues of model parameters.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150901
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
##submission.copyrightStatement##
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"150828 2015 eng "
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Two-Step Semidefinite Programming approach to clustering and dimensionality reduction
Macedo, Eloisa
University of Aveiro
Inspired by the recently proposed statistical technique called clustering and disjoint principal component analysis (CDPCA), we present in this paper a new algorithm for clustering objects and dimensionality reduction, based on Semidefinite Programming (SDP) models. The Two-Step-SDP algorithm is based on SDP relaxations of two clustering problems and on a K-means step in a reduced space. The Two-Step-SDP algorithm was implemented and tested in R, a widely used open source software. Besides returning clusters of both objects and attributes, the Two-Step-SDP algorithm returns the variance explained by each component and the component loadings. The numerical experiments on different data sets show that the algorithm is quite efficient and fast. Comparing to other known iterative algorithms for clustering, namely, the K-means and ALS algorithms, the computational time of the Two-Step-SDP algorithm is comparable to the K-means algorithm, and it is faster than the ALS algorithm.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150908
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
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"160601 2016 eng "
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Estimation Procedure for Reduced Rank Regression, PLSSVD
Álvarez, Willín
Universidad de Carabobo
Griffin, Victor John
Universidad de Carabobo
This paper presents a procedure for coefficient estimation in a multivariate regression model of reduced rank in the presence of multicollinearity. The procedure permits the prediction of the dependent variables taking advantage of both Partial Least Squares (PLS) and Singular Value Decomposition (SVD) methods, which is denoted by PLSSVD. Global variability indices and prediction error sums are used to compare the results obtained by classical regression with reduced rank (OLSSVD) and the PLSSVD procedure when applied to examples with different grades of multicollinearity (severe, moderate and low). In addition, simulations to compare the methods were performed with different sample sizes under four scenarios. The new PLSSVD method is shown to be more effective when the multicollinearity is severe and especially for small sample sizes.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160602
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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oai:ojs.localhost:article/149
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"150828 2015 eng "
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Interpolation Problem for Stationary Sequences with Missing Observations
Moklyachuk, Mikhail
Kyiv National Taras Shevchenko University http://probability.univ.kiev.ua/index.php?page=userinfo&person=mmp&lan=en
Sidei, Maria
Kyiv National Taras Shevchenko University
The problem of the mean-square optimal estimation of the linear functional $A_s\xi=\sum\limits_{l=0}^{s-1}\sum\limits_{j=M_l}^{M_l+N_{l+1}}a(j)\xi(j),$ $M_l=\sum\limits_{k=0}^l (N_k+K_k),$ \, $N_0=K_0=0,$ which depends on the unknown values of a stochastic stationary sequence $\xi(k)$ from observations of the sequence at points of time $j\in\mathbb{Z}\backslash S $, $S=\bigcup\limits_{l=0}^{s-1}\{ M_{l}, M_{l}+1, \ldots, M_{l}+N_{l+1} \}$ is considered. Formulas for calculating the mean-square error and the spectral characteristic of the optimal linear estimate of the functional are derived under the condition of spectral certainty, where the spectral density of the sequence $\xi(j)$ is exactly known. The minimax (robust) method of estimation is applied in the case where the spectral density is not known exactly, but sets of admissible spectral densities are given. Formulas that determine the least favorable spectral densities and the minimax spectral characteristics are derived for some special sets of admissible densities.
International Academic Press
2015-08-28 08:13:49
application/pdf
http://www.iapress.org/index.php/soic/article/view/20150906
Statistics, Optimization & Information Computing; Vol 3 No 3 (2015)
eng
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A Trivial Linear Discriminant Function
Shinmura, Shuichi
Seikei University, Faculty of Economics https://mail.google.com/mail/u/0/?tab=wm#inbox/14edc0b75697950a
In this paper, we focus on the new model selection procedure of the discriminant analysis. Combining re-sampling technique with k-fold cross validation, we develop a k-fold cross validation for small sample method. By this breakthrough, we obtain the mean error rate in the validation samples (M2) and the 95\% confidence interval (CI) of discriminant coefficient. Moreover, we propose the model selection procedure in which the model having a minimum M2 was chosen to the best model. We apply this new method and procedure to the pass/ fail determination of exam scores. In this case, we fix the constant =1 for seven linear discriminant functions (LDFs) and several good results were obtained as follows: 1) M2 of Fisher's LDF are over 4.6\% worse than Revised IP-OLDF. 2) A soft-margin SVM for penalty c=1 (SVM1) is worse than another mathematical programming (MP) based LDFs and logistic regression . 3) The 95\% CI of the best discriminant coefficients was obtained. Seven LDFs except for Fisher's LDF are almost the same as a trivial LDF for the linear separable model. Furthermore, if we choose the median of the coefficient of seven LDFs except for Fisher's LDF, those are almost the same as the trivial LDF for the linear separable model.
International Academic Press
2015-11-28 19:49:27
application/pdf
http://www.iapress.org/index.php/soic/article/view/20151202
Statistics, Optimization & Information Computing; Vol 3 No 4 (2015)
eng
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"160228 2016 eng "
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Matrix Factorizations based on induced norms
Choulakian, Vartan Ohanes
Université de Moncton
We decompose a matrix Y into a sum of bilinear terms in a stepwise manner, by considering Y as a mapping between two finite dimensional Banach spaces. We provide transition formulas, and represent them in a duality diagram, thus generalizing the well known duality diagram in the french school of data analysis. As an application, we introduce a family of Euclidean multidimensional scaling models.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160301
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
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oai:ojs.localhost:article/166
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"160601 2016 eng "
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Relaxed resolvent operator for solving a variational inclusion problem
Ahmad, Iqbal
Aligarh Muslim University, Aligarh, India
Rahaman, Mijanur
Aligarh Muslim University, Aligarh, India
Ahmad, Rais
Aligarh Muslim University, Aligarh, India
In this paper, we introduce a new resolvent operator and we call it relaxed resolvent operator. We prove that relaxed resolvent operator is single-valued and Lipschitz continuous and finally we appropriate the solution of a variational inclusion problem in Hilbert spaces by defining an iterative algorithm based on relaxed resolvent operator. A few concepts like Lipschitz continuity and strong monotonicity are used to prove the main result of this paper. Thus, no strong conditions are used. Some examples are constructed.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160609
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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oai:ojs.localhost:article/167
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"160228 2016 eng "
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A cubic B-spline Galerkin approach for the numerical simulation of the GEW equation
Karakoç, S. Battal Gazi
Nevşehir Hacı Bektaş Veli University
Zeybek, Halil
Abdullah Gül University
The generalized equal width (GEW) wave equation is solved numerically by using lumped Galerkin approach with cubic B-spline functions. The proposed numerical scheme is tested by applying two test problems including single solitary wave and interaction of two solitary waves. In order to determine the performance of the algorithm, the error norms L2 and L∞ and the invariants I1, I2 and I3 are calculated. For the linear stability analysis of the numerical algorithm, von Neumann approach is used. As a result, the obtained findings show that the presented numerical scheme is preferable to some recent numerical methods.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160303
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/171
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"160601 2016 eng "
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Second-order optimality and duality in vector optimization over cones
Suneja, Surjeet Kaur
Miranda House, University of Delhi, India
Sharma, Sunila
Miranda House, University of Delhi, India
Kapoor, Malti
Motilal Nehru College, University of Delhi, India
In this paper, we introduce the notion of a second-order cone- convex function involving second-order directional derivative. Also, second-order cone-pseudoconvex, second-order cone-quasiconvex and other related functions are defined. Second-order optimality and Mond-Weir type duality results are derived for a vector optimization problem over conesnusing the introduced classes of functions.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160607
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/172
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"160228 2016 eng "
2310-5070
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Filtering Problem for Functionals of Stationary Sequences
Moklyachuk, Mikhail
Kyiv National Taras Shevchenko University http://probability.univ.kiev.ua/index.php?page=userinfo&person=mmp&lan=en
Luz, Maksym
Kyiv National Taras Shevchenko University
In this paper, we consider the problem of the mean-square optimal linear estimation of functionals which depend on the unknown values of a stationary stochastic sequence from observations with noise. In the case of spectral certainty in which the spectral densities of the sequences are exactly known, we propose formulas for calculating the spectral characteristic and value of the mean-square error of the estimate by using the Fourier coefficients of some functions from the spectral densities. When the spectral densities are not exactly known but a class of admissible spectral densities is given, the minimax-robust method of estimation is applied. Formulas for determining the least favourable spectral densities and the minimax-robust spectral characteristics of the optimal estimates of the functionals are proposed for some specific classes of admissible spectral densities.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160306
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/175
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"160601 2016 eng "
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Optimality and duality in set-valued optimization using higher-order radial derivatives
Yu, Guolin
Kong, Xiangyu
This paper is devoted to the study of optimality conditions and duality theory for a set-valued optimization problem. by using the higher-order radial derivative of a set-valued map, we establish Fritz John and Kuhn-Tucker types necessary and sufficient optimality conditions for a weak minimizer of a set-valued optimization problem under the assumption that set-valued maps in the formulation of objective and constraint maps are near cone-subconvexlike. As an application of the optimality conditions, we prove weak, strong and converse duality theorems for Mond-Weir and Wolfe types dual problems.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160606
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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oai:ojs.localhost:article/178
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"160601 2016 eng "
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The Best Model of the Swiss Banknote Data -Validation by the 95% CI of coefficients and t-test of discriminant scores
Shinmura, Shuichi
Seikei Univ. http://researchmap.jp/read0049917/?lang=english
The discriminant analysis is not the inferential statistics since there are no equations for standard error (SE) of error rate and discriminant coefficient based on the normal distribution. In this paper, we proposed the “k-fold cross validation for small sample” and can obtain the 95% confidence interval (CI) of error rates and discriminant coefficients. This method is the computer-intensive approach by statistical and mathematical programming (MP) software such as JMP and LINGO. By the proposed approach, we can choose the best model with the minimum mean of error rate in the validation samples (Minimum M2 Standard). In this research, we examine the sixteen linear separable models of Swiss banknote data by eight linear discriminant functions (LDFs). M2 of the best model of Revised IP-OLDF is the smallest value of all models. We find all coefficients of six Revised IP-OLDF among sixteen models rejected by the 95% CI of discriminant coefficients (Discriminant coefficient standard). We compare t-values of the discriminant scores. The t-value of the best model has the maximum values among sixteen models (Maximum t-value Standard). Moreover, we can conclude that all standards support the best model of Revised IP-OLDF.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160603
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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"160601 2016 eng "
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Morgenstern type bivariate Lindley Distribution
Vaidyanathan, V S
Pondicherry University
Puducherry, India
Varghese, A, Sharon
Pondicherry University
Puducherry, India
In this paper, a bivariate Lindley distribution using Morgenstern approach is proposed which can be used for modeling bivariate life time data. Some characteristics of the distribution like moment generating function, joint moments, Pearson correlation coefficient, survival function, hazard rate function, mean residual life function, vitality function and stress-strength parameter R=Pr(Y<X), are derived. The conditions under which the proposed distribution is an increasing (decreasing) failure rate distribution and positive (negative) quadrant dependent is discussed. Also, the method of estimating model parameters and stress-strength parameter by maximum likelihood is elucidated. Numerical illustration using simulated data is carried out to access the estimates in terms of mean squared error and relative absolute bias.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160604
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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"160228 2016 eng "
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Generalized Second-Order Parametric Optimality Conditions in Semiinfinite Discrete Minmax Fractional Programming and Second-Order Univexity
Verma, Ram
University of North Texas
Zalmai, G.
Northern Michigan University
This paper deals with mainly establishing numerous sets of generalized second order paramertic sufficient optimality conditions for a semiinfinite discrete minmax fractional programming problem, while the results on semiinfinite discrete minmax fractional programming problem achieved based on some partitioning schemes under various types of generalized second order univexity assumptions.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160302
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
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"160601 2016 eng "
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Memetic Algorithm and its Application to the Arrangement of Exam Timetable
Huang, Wenhua
Yi, Guisheng
He, Sulan
This paper looks at Memetic Algorithm for solving timetabling problems. We present a new memetic algorithm which consists of global search algorithm and local search algorithm. In the proposed method, a genetic algorithm is chosen for global search algorithm while a simulated annealing algorithm is used for local search algorithm. In particular, we could get an optimal solution through the .NET with the real data of JiangXi Normal University. Experimental results show that the proposed algorithm can solve the university exam timetabling problem efficiently.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160605
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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"160601 2016 eng "
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Efficient Experimental Design Strategies in Toxicology and Bioassay
O'Brien, Timothy E.
Loyola University Chicago, USA http://webpages.math.luc.edu/~tobrien/
Modelling in bioassay often uses linear or nonlinear logistic regression models, and relative potency is often the focus when two or more compounds are to be compared. Estimation in these settings is typically based on likelihood methods. Here, we focus on the 3-parameter model representation given in Finney (1978) in which the relative potency is a model parameter. Using key matrix results and the general equivalence theorem of Kiefer & Wolfowitz (1960), this paper establishes key design properties of the optimal design for relative potency using this model. We also highlight aspects of subset designs for the relative potency parameter and extend geometric designs to efficient design settings of bioassay. These latter designs are thus useful for both parameter estimation and checking for goodness-of-fit. A typical yet insightful example is provided from the field of toxicology to illustrate our findings.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160601
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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"160601 2016 eng "
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Two-Step Proximal Gradient Algorithm for Low-Rank Matrix Completion
Wang, Qiuyu
Henan University
Cao, Wenjiao
Henan University
Jin, Zhengfen
Henan University of Science and Technology
In this paper, we propose a two-step proximal gradient algorithm to solve nuclear norm regularized least squares for the purpose of recovering low-rank data matrix from sampling of its entries. Each iteration generated by the proposed algorithm is a combination of the latest three points, namely, the previous point, the current iterate, and its proximal gradient point. This algorithm preserves the computational simplicity of classical proximal gradient algorithm where a singular value decomposition in proximal operator is involved. Global convergence is followed directly in the literature. Numerical results are reported to show the efficiency of the algorithm.
International Academic Press
2016-06-01 15:51:14
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160608
Statistics, Optimization & Information Computing; Vol 4 No 2 (2016)
eng
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"160228 2016 eng "
2310-5070
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A Splitting-based Iterative Method for Sparse Reconstruction
Kang, Liquan
Chen, Ying
Yu, Zefeng
Wu, Heng
Zheng, Zijun
Niu, Shanzhou
In this paper, we study a ℓ1-norm regularized minimization method for sparse solution recovery in compressed sensing and X-ray CT image reconstruction. In the proposed method, an alternating minimization algorithm is employed to solve the involved ℓ1-norm regularized minimization problem. Under some suitable conditions, the proposed algorithm is shown to be globally convergent. Numerical results indicate that the presented method is effective and promising.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160305
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
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"160228 2016 eng "
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An improved partial bundle method for linearly constrained minimax problems
Tang, Chunming
Guangxi University
Chen, Huangyue
Guangxi University
Jian, Jinbao
Yulin Normal University
In this paper, we propose an improved partial bundle method for solving linearly constrained minimax problems. In order to reduce the number of component function evaluations, we utilize a partial cutting-planes model to substitute for the traditional one. At each iteration, only one quadratic programming subproblem needs to be solved to obtain a new trial point. An improved descent test criterion is introduced to simplify the algorithm. The method produces a sequence of feasible trial points, and ensures that the objective function is monotonically decreasing on the sequence of stability centers. Global convergence of the algorithm is established. Moreover, we utilize the subgradient aggregation strategy to control the size of the bundle and therefore overcome the difficulty of computation and storage. Finally, some preliminary numerical results show that the proposed method is effective.
International Academic Press
2016-02-28 13:41:10
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160307
Statistics, Optimization & Information Computing; Vol 4 No 1 (2016)
eng
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"160830 2016 eng "
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A Comparison of Compressed Sensing and Sparse Recovery Algorithms Applied to Simulation Data
Fan, Ya Ju
Lawrence Livermore National Laboratory
Kamath, Chandrika
Lawrence Livermore National Laboratory
The move toward exascale computing for scientific simulations is placing new demands on compression techniques. It is expected that the I/O system will not be able to support the volume of data that is expected to be written out. To enable quantitative analysis and scientific discovery, we are interested in techniques that compress high-dimensional simulation data and can provide perfect or near-perfect reconstruction. In this paper, we explore the use of compressed sensing (CS) techniques to reduce the size of the data before they are written out. Using large-scale simulation data, we investigate how the sufficient sparsity condition and the contrast in the data affect the quality of reconstruction and the degree of compression. We provide suggestions for the practical implementation of CS techniques and compare them with other sparse recovery methods. Our results show that despite longer times for reconstruction, compressed sensing techniques can provide near perfect reconstruction over a range of data with varying sparsity.
International Academic Press
2016-08-30 14:34:52
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160901
Statistics, Optimization & Information Computing; Vol 4 No 3 (2016)
eng
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"161207 2016 eng "
2310-5070
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Characterization of Generalized Invexity in Multiobjective Fractional Variational Problem
Kumar, Promila
Dagar, Jyoti
Sharma, Bharti
In this article we define certain conditions on the functionals of multi-objective fractional variational problem in order that it becomes F-Kuhn Tucker pseudo invex or F-Fritz John pseudo invex. We also define F-KT and F-FJ points. Further, these problems are characterized such that all F-KT and F-FJ points become efficient solutions for the featured problem. An example is presented to verify the existence of F-KT point. A Parametric dual is proposed and various duality results are proved under the assumption of F-KT as well as F-FJ pseudo invexity.
International Academic Press
2016-12-07 10:20:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/20161205
Statistics, Optimization & Information Computing; Vol 4 No 4 (2016)
eng
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On Size Biased Kumaraswamy Distribution
Sharma, Dreamlee
Department of Statistics
North-Eastern Hill University
Shillong, Meghalaya
India
Chakrabarty, Tapan Kumar
Department of Statistics
North-Eastern Hill University
Shillong, Meghalaya
India
In this paper, we introduce and study the size-biased form of Kumaraswamy distribution. The Kumaraswamy distribution which has drawn considerable attention in hydrology and related areas was proposed by Kumarswamy. The new distribution is derived under sizebiased probability of sampling taking the weights as the variate values. Various distributional and characterizing properties of the model are studied. The methods of maximum likelihood and matching quantiles estimation are employed to estimate the parameters of the proposed model. Finally, we apply the proposed model to simulated and real data sets.
International Academic Press
2016-08-30 14:34:52
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160905
Statistics, Optimization & Information Computing; Vol 4 No 3 (2016)
eng
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"160830 2016 eng "
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A statistical model of macromolecules dynamics for Fluorescence Correlation Spectroscopy data analysis
Koroliouk, Dmitri
Institute of Telecommunications and Global Information Space of Ukrainian Acad. Sciences, Kiev, Ukraine
Koroliuk, Vladimir Semenovich
Institute of Mathematics of Ukrainian Acad. Sciences, Kiev, Ukraine
Nicolai, Eleonora
Department of Experimental Medicine and Surgery, University of Rome Tor Vergata, 00133 Rome, Italy
Bisegna, Paolo
Department of Civil Engineering, University of Rome Tor Vergata, 00133 Rome, Italy
Stella, Lorenzo
Department of Science and Chemical Technology, University of Rome Tor Vergata
Rosato, Nicola
Department of Experimental Medicine and Surgery, University of Rome Tor Vergata, 00133 Rome, Italy
In this paper, we propose a new mathematical model to describe the mechanisms of biological macromolecules interactions. Our model consists of a discrete stationary random sequence given by a solution of difference stochastic equation, characterized by a drift predictive component and by a diffusion term. The relative statistical estimations are very simple and effective, promising to be a good tool for the mathematical description of collective biological reactions. This paper presents the mathematical model and its verification on a simulated data set, obtained on the basis of the well-known Stokes-Einsteinmodel. In particular, we considered several mix of particles of different diffusion coefficient, respectively: D1=10 mm2/sec and D2=100 mm2/sec. The parameters evaluated by this new mathematical model on simulated data show good estimation accuracy, in comparison with the prior parameters used in the simulations. Furthermore, when analyzing the data for the mix of particles with different diffusion coefficient, the proposed model parameters (regression) and (square variance of the stochastic component) have a good discriminative ability for the molar fraction determination. In this paper, we propose a new mathematical model to describe the mechanisms of biological macromolecules interactions. Our model consists of a discrete stationary random sequence given by a solution of difference stochastic equation, characterized by a drift predictive component and by a diffusion term. The relative statistical estimations are very simple and effective, promising to be a good tool for mathematical description of collective biological reactions. This paper presents the mathematical model and its verification on simulated data set, obtained on the basis of the well-known Stokes-Einsteinmodel. In particular we considered several mix of particles of different diffusion coefficient, respectively: D1=10 mm2/sec and D2=100 mm2/sec. The parameters evaluated by this new mathematical model on simulated data, show good estimation accuracy, in comparison with the a-priori parameters used in the simulations. Furthermore, when analyzing the data for mix of particles with different diffusion coefficient, the proposed model parameters (regression) and (square variance of stochastic component) have a good discriminative ability for the molar fraction determination.
International Academic Press
2016-08-30 14:34:52
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160903
Statistics, Optimization & Information Computing; Vol 4 No 3 (2016)
eng
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"160830 2016 eng "
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A Criterion for Testing Hypothesis about Impulse Response Function
Rozora, Iryna
National Taras Shevchenko University of Kyiv
Kozachenko, Yu. V
Taras Shevchenko National University of Kyiv
In this paper a time-invariant continuous linear system with a real-valued impulse response function is considered. A new method for the estimator construction of the impulse response function is proposed. Two criteria on the shape of the impulse response function are given. In this paper a time-invariantcontinuous linear system with a real-valued impulse response function is considered. A new method for the estimator construction of the impulse response function is proposed. Two criteria on the shape of the impulse response function are given.
International Academic Press
2016-08-30 14:34:52
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160902
Statistics, Optimization & Information Computing; Vol 4 No 3 (2016)
eng
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"161207 2016 eng "
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Mixed input and output orientations of Data Envelopment Analysis with Linear Fractional Programming and Least Distance Measures
Dar, Qaiser Farooq
Department of Statistics
Pondicherry University
kalapet pondicherry-605014
Padi, Tirupathi Rao
Department of Statistics
Pondicherry University
kalapet pondicherry-605014
Tali, Arif Muhammad
Department of Statistics,
Pondicherry University,
kalapet pondicherry-605014.
Data Envelopment Analysis (DEA) is an optimization technique to evaluate the efficiency of Decision- Making Units (DMU’s) together with multiple inputs and multiple outputs on the strength of weighted input and output ratios, where as Linear fractional programming is used to obtain DEA frontier. The efficiency scores of DMU obtained through either input orientation or output orientation DEA model will provide only local optimum solution. However, the mixed orientation of input and output variables will provide the global optimal solution for getting the efficient DMUs in DEA. This study has proposed the relationships of a mixed orientation of input and output variables using fractional linear programming along with Least-Distance Measure (LDM). Both constant returns to scale (CRS) and variable returns to scale (VRS) are considered for the comparative study.
International Academic Press
2016-12-07 10:20:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/20161204
Statistics, Optimization & Information Computing; Vol 4 No 4 (2016)
eng
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"160830 2016 eng "
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Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method
Xue, Wei
Nanjing University of Science and Technology
Zhang, Wensheng
Chinese Academy of Sciences
We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.
International Academic Press
2016-08-30 14:34:52
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160904
Statistics, Optimization & Information Computing; Vol 4 No 3 (2016)
eng
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Nonmonotone Spectral Gradient Method for l_1-regularized Least Squares
Cheng, Wanyou
Donggguan University of Technology
Hu, Qingjie
In the paper, we investigate a linear constraint optimization reformulation to a more general form of the l_1 regularization problem and give some good properties of it. We first show that the equivalence between the linear constraint optimization problem and the l_1 regularization problem. Second, the KKT point of the linear constraint problem always exists since the constraints are linear; we show that the half constraints must be active at any KKT point. In addition, we show that the KKT points of the linear constraint problem are the same as the stationary points of the l_1 regularization problem. Based on the linear constraint optimization problem, we propose a nonomotone spectral gradient method and establish its global convergence. Numerical experiments with compressive sense problems show that our approach is competitive with several known methods for standard l_2-l_1 problem.
International Academic Press
2016-08-30 14:34:52
application/pdf
http://www.iapress.org/index.php/soic/article/view/20160906
Statistics, Optimization & Information Computing; Vol 4 No 3 (2016)
eng
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"170601 2017 eng "
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Relations for Moments of Generalized Record Values from Additive Weibull Distribution and Associated Inference
Khan, Rafiqullah
Aligarh Muslim University, Aligarh
Khan, M.A
Aligarh Muslim University, Aligarh
Khan, M.A.R
Aligarh Muslim University, Aligarh
In this note we give some simple recurrence relations satisfied by single and product moments of k-th upper record values from the additive Weibull distribution. These relations are deduced for moments of upper record values. Further, conditional expectation and recurrence relation for single moments are used to characterize the additive Weibull distribution.
International Academic Press
2017-06-01 09:54:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic170605
Statistics, Optimization & Information Computing; Vol 5 No 2 (2017)
eng
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"170829 2017 eng "
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System of nonlinear variational inclusion problems with $(A,\eta)$-maximal monotonicity in Banach spaces
Sahu, Nabin Kumar
Dhirubhai Ambani Institute of Information and Communication Technology, Gandhinagar, India
Mahato, N. K.
PDPM IIITDM, Jabalpur, India
Mohapatra, R. N.
University of Central Florida, Orlando, FL. 32816,
USA
This paper deals with a new system of nonlinear variational inclusion problems involving $(A,\eta)$-maximal relaxed monotone and relative $(A,\eta)$-maximal monotone mappings in 2-uniformly smooth Banach spaces. Using the generalized resolvent operator technique, the approximation solvability of the proposed problem is investigated. An iterative algorithm is constructed to approximate the solution of the problem. Convergence analysis of the proposed algorithm is investigated. Similar results are also proved for other system of variational inclusion problems involving relative $(A,\eta)$-maximal monotone mappings and $(H,\eta)$-maximal monotone mappings.
International Academic Press
2017-09-01 13:45:08
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic20170906
Statistics, Optimization & Information Computing; Vol 5 No 3 (2017)
eng
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"161207 2016 eng "
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Filtering Problem for Stationary Sequences with Missing Observations
Moklyachuk, Mikhail
Kyiv National Taras Shevchenko University http://probability.univ.kiev.ua/index.php?page=userinfo&person=mmp&lan=en
Sidei, Maria
Kyiv National Taras Shevchenko University
We deal with the problem of the mean-square optimal linear estimation of linear functionals which depend on the unknown values of a stationary stochastic sequence from observations of the sequence with a stationary noise sequence. Formulas for calculating the mean-square errors and the spectral characteristics of the optimal linear estimates of functionals are derived under the condition of spectral certainty, where spectral densities of the sequences are exactly known. The minimax (robust) method of estimation is applied in the case of spectral uncertainty, where spectral densities are not known exactly while sets of admissible spectral densities are given. Formulas that determine the least favorable spectral densities and the minimax spectral characteristics are proposed for some special sets of admissible densities.
International Academic Press
2016-12-07 10:20:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/20161203
Statistics, Optimization & Information Computing; Vol 4 No 4 (2016)
eng
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"161207 2016 eng "
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Approximations of the solutions of a stochastic differential equation using Dirichlet process mixtures and Gaussian mixtures
Infante, Saba
Department of Mathematics, Faculty of Science and Technology, University of Carabobo, Venezuela
Luna, César
Department of Mathematics, Faculty of Science and Technology, University of Carabobo, Venezuela
Sánchez, Luis
Department of Mathematics, Faculty of Education. University of Carabobo, Venezuela
Hernández, Aracelis
Department of Mathematics, Faculty of Science and Technology, University of Carabobo, Venezuela
Stochastic differential equations arise in a variety of contexts. There are many techniques for approximation of the solutions of these equations that include statistical methods, numerical methods, and other approximations. This article implements a parametric and a nonparametric method to approximate the probability density of the solutions of stochastic differential equation from observations of a discrete dynamic system. To achieve these objectives, mixtures of Dirichlet process and Gaussian mixtures are considered. The methodology uses computational techniques based on Gaussian mixtures filters, nonparametric particle filters and Gaussian particle filters to establish the relationship between the theoretical processes of unobserved and observed states. The approximations obtained by this proposal are attractive because the hierarchical structures used for modeling are flexible, easy to interpret and computationally feasible. The methodology is illustrated by means of two problems: the synthetic Lorenz model and a real model of rainfall. Experiments show that the proposed filters provide satisfactory results, demonstrating that the algorithms work well in the context of processes with nonlinear dynamics which require the joint estimation of states and parameters. The estimated measure of goodness of fit validates the estimation quality of the algorithms.
International Academic Press
2016-12-07 10:20:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/20161202
Statistics, Optimization & Information Computing; Vol 4 No 4 (2016)
eng
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oai:ojs.localhost:article/244
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"170601 2017 eng "
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A net with serial access and the reduction of total work for identical service
Pavlov, Andrey Valerianovich
Moscow Institute of Radiotechnics Electronica and Automatics (Moscow Tech.University),Russia.Moscow.pr.Vernadskogo,78,higher mathematica-1
This paper looks at the open net in conditions of identical service. The strong reduction of total work and time of expectation on the inlying nodes of net is marked. By using the transform of Legendre, the previous results are generalized on net with the relatively general structure.
International Academic Press
2017-06-01 09:54:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic170604
Statistics, Optimization & Information Computing; Vol 5 No 2 (2017)
eng
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nmb a2200000Iu 4500
"170304 2017 eng "
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A stochastic predator-prey system with Watt-type functional response
Nguyen, Dung Tien
FPT University
In this paper we consider a stochastic version of predator-prey systems with Watt-type functional response. We first prove the existence and uniqueness of the positive global solution by using the comparison theorem of stochastic equations. Then, we study the boundedness of moments of the solution. Furthermore, the growth rates, persistence and extinction of species are investigated.
International Academic Press
2017-03-04 04:43:47
application/pdf
http://www.iapress.org/index.php/soic/article/view/20170304
Statistics, Optimization & Information Computing; Vol 5 No 1 (2017)
eng
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"170304 2017 eng "
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Modified random errors S-iterative process for stochastic fixed point theorems in a generalized convex metric space
Saipara, Plern
KMUTT Fixed Point Research Laboratory,
Department of Mathematics, King Mongkut's University of Technology Thonburi, Thailand
Kumam, Wiyada
Program in Applied Statistics,
Department of Mathematics and Computer Science, Faculty of Science and Technology, Rajamangala University of Technology Thanyaburi, Thailand http://poomkumam.wordpress.com/
Chaipunya, Parin
KMUTT Fixed Point Research Laboratory,
Department of Mathematics, King Mongkut's University of Technology Thonburi, Thailand
In this paper, we suggest the modified random S-iterative process and prove the common random fixed point theorems of a finite family of random uniformly quasi-Lipschitzian operators in a generalized convex metric space. Our results improves and extends various results in the literature.
International Academic Press
2017-03-04 04:43:47
application/pdf
http://www.iapress.org/index.php/soic/article/view/20170306
Statistics, Optimization & Information Computing; Vol 5 No 1 (2017)
eng
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2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"170304 2017 eng "
2310-5070
2311-004X
dc
A Direct Local Search Method and its Application to a Markovian Model
Taushanov, Zhivko
University of Lausanne
Berchtold, André
University of Lausanne
While the hidden mixture transition distribution (HMTD) model is a powerful framework for the description, analysis, and classification of longitudinal sequences of continuous data, it is notoriously difficult to estimate because of the complexity of its solution space. In this paper, we explore how a new heuristic specifically developed for the HMTD performs compared to different standard optimization algorithms. This specific heuristic can be classified as a hill-climbing method, and different variants are proposed, including a jittering procedure to escape local maxima and measures to speed up the convergence.
Different popular approaches are used for comparison, including PSO, SA, GA, NM, L-BFGS-B, and DE. The same HMTD model was optimized on different datasets and the results were compared in terms of both fit to the data and estimated parameters. Even if the complexity of the problem implies that no one algorithm can be considered as an overall best, our heuristic performed well in all situations, leading to useful solutions in terms of both fit and interpretability.
International Academic Press
2017-03-04 04:43:47
application/pdf
http://www.iapress.org/index.php/soic/article/view/20170302
Statistics, Optimization & Information Computing; Vol 5 No 1 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/254
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"161207 2016 eng "
2310-5070
2311-004X
dc
Robust C-optimal Design For Estimating Multiple EDps Under The 4-parameter Logistic Model
Zhang, Anqing
North Dakota State University
Hyun, Seung Won
North Dakota State University
The four-parameter logistic model is often used to describe dose-response functions in many toxicological studies. In this study, under the four-parameter logistic model, optimal designs to estimate the EDp are studied. The EDp is the dose achieving p% of the expected difference between the maximum and the minimum responses. C-optimal design works the best for estimating the EDp, but the best performance is only guaranteed when the goal is for estimating a single EDp. If the c-optimal design for studying a specific EDp is used for studying different EDp values, it may work poorly. This paper shows that the c-optimal design for estimating the EDp truly depends on the value of p under the 4-parameter logistic model. We present a robust c-optimal design that works well for the change in the value of p, so that the design can be used effectively for studying multiple EDp values. In addition, this paper presents a two-stage robust c-optimal design for estimating multiple EDp that is not substantially affected by the mis-specified nominal parameter values.
International Academic Press
2016-12-07 10:20:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/20161201
Statistics, Optimization & Information Computing; Vol 4 No 4 (2016)
eng
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oai:ojs.localhost:article/255
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"170601 2017 eng "
2310-5070
2311-004X
dc
Evidences in lifetimes of sequential r-out-of-n systems and optimal sample size determination for Burr XII populations
Hashempour, Majid
Department of Statistics, School of Science, University of Hormozgan, Bandar Abbas, Iran
In this paper, statistical evidences in lifetimes of sequential r-out-of-n systems, which are modelled by sequential order statistics (SOS), are studied. Weak and misleading evidences in SOS for hypotheses about the population parameter are derived in explicit expressions and their behaviours with respect to the model parameters are investigated in details. Optimal sample sizes given a minimum desired level for the decisive and the correct probabilities are provided. It is shown that the optimal sample size does not depend on some model parameters.
International Academic Press
2017-06-01 09:54:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic170607
Statistics, Optimization & Information Computing; Vol 5 No 2 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/260
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"170304 2017 eng "
2310-5070
2311-004X
dc
Dynamic Programming Algorithms on Directed Cographs
Gurski, Frank
University of Duesseldorf http://www.cs.hhu.de/en/research-groups/algorithmics-for-hard-problems.html
In this paper we consider directed cographs, which are defined by Bechet et al. by the disjoint union, series, and order composition, from an algorithmic point of view. Using their recursive structure we give dynamic programming algorithms to show that for every directed cograph the size of a largest edgeless subdigraph, the size of a largest subdigraph which is a tournament, the size of a largest semicomplete subdigraph, and the size of a largest complete subdigraph can be computed in linear time. Our main results show that the hamiltonian path, hamiltonian cycle, regular subdigraph, and directed cut problem are polynomial on directed cographs.
International Academic Press
2017-03-04 04:43:47
application/pdf
http://www.iapress.org/index.php/soic/article/view/20170303
Statistics, Optimization & Information Computing; Vol 5 No 1 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/262
2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"170304 2017 eng "
2310-5070
2311-004X
dc
Explicit form of global solution to stochastic logistic differential equation and related topics
Borysenko, Dmytro
Department of Integral and Differential Equations, Taras Shevchenko National University of Kyiv, Ukraine
Borysenko, Oleksandr
Department of Probability Theory, Statistics and Actuarial Mathematics, Taras Shevchenko National University of Kyiv
This paper presents the explicit form of positive global solution to stochastically perturbed nonautonomous logistic equation $$dN(t)=N(t)\left[(a(t)-b(t)N(t))dt+\alpha(t)dw(t)+\int_{\mathbb{R}}\gamma(t,z)\tilde\nu(dt,dz)\right],\ N(0)=N_0,$$ where $w(t)$ is the standard one-dimensional Wiener process, $\tilde\nu(t,A)=\nu(t,A)-t\Pi(A)$, $\nu(t,A)$ is the Poisson measure, which is independent on $w(t)$, $E[\nu(t,A)]=t\Pi(A)$, $\Pi(A)$ is a finite measure on the Borel sets in $\mathbb{R}$. If coefficients $a(t), b(t), \alpha(t)$ and $\gamma(t,z)$ are continuous on $t$, $T$-periodic on $t$ functions, $a(t)>0, b(t)>0$ and $$\int_{0}^{T}\left[a(s)-\alpha^2(s)-\int_{\mathbb{R}}\frac{\gamma^2(s,z)}{1+\gamma(s,z)}\Pi(dz)\right]ds>0,$$ then there exists unique, positive $T$-periodic solution to equation for $E[1/N(t)]$.
International Academic Press
2017-03-04 04:43:47
application/pdf
http://www.iapress.org/index.php/soic/article/view/20170305
Statistics, Optimization & Information Computing; Vol 5 No 1 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/263
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nmb a2200000Iu 4500
"170601 2017 eng "
2310-5070
2311-004X
dc
Strictly $\varphi$-sub-Gaussian quasi shot noise processes
Vasylyk, Olga
Taras Shevchenko National University of Kyiv, Ukraine
In the paper, strictly $\varphi$-sub-Gaussian quasi shot noise processes are considered. There are obtained estimates for distribution of supremum of such a process defined on a compact set and formulated conditions for its sample functions continuity with probability one.
International Academic Press
2017-06-01 09:54:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic170603
Statistics, Optimization & Information Computing; Vol 5 No 2 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/264
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"170829 2017 eng "
2310-5070
2311-004X
dc
Bonus-Malus System Using Finite Mixture Models
MohammadPour, Saeed
Allameh Tabatabai University, Iran
Saeedi, Karzan
Allameh Tabatabai University, Iran
Mahmoudvand, Rahim
Bu-Ali Sina University, Iran
There is a vast literature on Bonus-Malus System (BMS), in which a policyholders responsible for positive claims will be penalised by a malus and the policyholders who had no claim will be rewarded by a bonus. In this paper, we present an optimal BMS using finite mixture models. We conduct a numerical study to compare the new model with the current BMS that use finite mixture models.
International Academic Press
2017-09-01 13:45:08
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic20170901
Statistics, Optimization & Information Computing; Vol 5 No 3 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/267
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"170829 2017 eng "
2310-5070
2311-004X
dc
Bootstrap Approach to the One-Sample and Two- Sample Test of Variances of a Fuzzy Random Variable
Chachi, Jalal
Semnan University
The aim of this paper is to present in a concise and integrated way of the bootstrap approach to statistical testing of hypotheses about the variance of fuzzy random variable. In this approach, first a notion of fuzzy random variables is recalled. Then, we will consider hypothesis-tests for the (crisp-valued) variance of fuzzy data in a population. For this purpose, the $\alpha$-pessimistic values of the imprecise observations are used for defining a new notion of distance measure between fuzzy data, which is then used to make a procedure for testing the statistical hypotheses. Based on this argument, the application of bootstrap techniques in dealing with these testing problems will be introduced. The procedure develops a non-parametric approach to testing statistical hypotheses based on one-sample and two-sample fuzzy data.
International Academic Press
2017-09-01 13:45:08
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic20170902
Statistics, Optimization & Information Computing; Vol 5 No 3 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/268
2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"170601 2017 eng "
2310-5070
2311-004X
dc
Robust Bayesian Analysis of Generalized Half Logistic Distribution
Chaturvedi, Ajit
University of Delhi
Kumari, Taruna
University of Delhi
In this paper, Robust Bayesian analysis of the generalized half logistic distribution (GHLD) under an $\epsilon$-contamination class of priors for the shape parameter $\lambda$ is considered. ML-II Bayes estimators of the parameters, reliability function and hazard function are derived under the squared-error loss function (SELF) and linear exponential (LINEX) loss function by considering the Type~II censoring and the sampling scheme of Bartholomew (1963). Both the cases when scale parameter is known and unknown is considered under Type~II censoring and under the sampling scheme of Bartholomew. Simulation study and analysis of a real data set are presented.
International Academic Press
2017-06-01 09:54:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic170608
Statistics, Optimization & Information Computing; Vol 5 No 2 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/276
2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"170601 2017 eng "
2310-5070
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dc
Proper complex random processes
Kozachenko, Yurii Vasilyevich
Taras Shevchenko National University of Kyiv, Vasyl' Stus Donetsk National University
Petranova, Marina Yurievna
Vasyl' Stus Donetsk National University
In this paper, the problem of proper complex random processes is studied. The behavior of the module stationary proper complex random process at infinity is developed. It was obtained the estimate of distribution functions from a module of stationary Gaussian proper complex random processes.
International Academic Press
2017-06-01 09:54:02
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic170606
Statistics, Optimization & Information Computing; Vol 5 No 2 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/277
2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"170304 2017 eng "
2310-5070
2311-004X
dc
New version of the MDR method for stratified samples
Bulinski, Alexander
Lomonosov Moscow State University, Russia
Kozhevin, Alexey
Lomonosov Moscow State University, Russia
The new version of the MDR method of performing identication of relevant factors within a given collection X_1,..., X_n is introduced for stratified samples in the case of binary response variable Y. We establish a criterion of strong consistency of estimates (involving K-cross-validation procedure and penalty) for a specified prediction error function. The cost approach is proposed to compare experiments with random and nonrandom number of observations. Analytic results are accompanied by simulations.
International Academic Press
2017-03-04 04:43:47
application/pdf
http://www.iapress.org/index.php/soic/article/view/20170301
Statistics, Optimization & Information Computing; Vol 5 No 1 (2017)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/278
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"180624 2018 eng "
2310-5070
2311-004X
dc
Flexiblity of Using Com-Poisson Regression Model for Count Data
AVCI, Esin
Giresun University
The Poisson regression model is the most common model for fitting count data. However, it is suitable only for modeling equi-dispersed distribution. The Conway-Maxwell-Poisson (COM-Poisson) regression model allows modeling over and under-dispersion distribution. The purpose of this study is to demonstrate the flexibility of the Conway-Maxwell-Poisson (COM-Poisson) regression model on simulation and alg data.
International Academic Press
2018-06-24 18:36:13
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic20180610
Statistics, Optimization & Information Computing; Vol 6 No 2 (2018)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/281
2022-01-21T18:20:03Z
soic:ART
nmb a2200000Iu 4500
"181102 2018 eng "
2310-5070
2311-004X
dc
Improved Mean Methods of Imputation
Mohamed, Choukri
A. Sedory, Stephen
Singh, Sarjinder
Texas A&M University - Kingsville
Replacing missing values of a variable with the mean of the non-missing values is a simple and natural way to impute values fortunately in the case where data is missing completely at random. Following a short review of this method we consider thus possible improvements, are called the shrinkage method, a second called the weighted interval method, and a third called the known variance method. Estimates of the population mean obtained from each of these methods are compared to the mean method both analytically and by means of numerical examples.
International Academic Press
2018-11-02 09:27:46
application/pdf
http://www.iapress.org/index.php/soic/article/view/20181203
Statistics, Optimization & Information Computing; Vol 6 No 4 (2018)
eng
##submission.copyrightStatement##
oai:ojs.localhost:article/283
2022-01-21T18:20:03Z
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nmb a2200000Iu 4500
"170829 2017 eng "
2310-5070
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dc
New Class of Duality Models in Discrete Minmax Fractional Programming Based on Second-Order Univexities
Verma, Ram
International Publications USA
Antczak, Tdeusz
University of Lodz
The main goal of this paper is first to formulate four new general higher order parametric duality models for a discrete minmax fractional programming problem, and then prove appropriate duality theorems applying various new classes of second order univex functions.
International Academic Press
2017-09-01 13:45:08
application/pdf
http://www.iapress.org/index.php/soic/article/view/soic20170907
Statistics, Optimization & Information Computing; Vol 5 No 3 (2017)
eng
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