Buys-Ballot Technique for the Analysis of Time Series with a Cubic-Trend Component

  • Emmanuel Okereke
Keywords: Buys-Ballot Methods, Cubic trend, auto correlation structure, pairwise-negatively correlated estimators, invertible third-order moving average model

Abstract

Time series, especially those with the cubic trend component, are encountered in many data analysis situations. The decomposition of such series into various components requires a method that can adequately estimate the cubic trend as well as other components of the series.  In this study, the chain base, fixed base and  classical methods of decomposition of time series with the cubic trend component are discussed with emphasis on the additive model. Chain base and fixed base estimators of the additive model parameters are derived. Basic properties of these two classes of estimators are equally determined. The derived chain base variables have the autocorrelation structure of an invertible third-order moving average model. The chain base estimators are found to be pairwise-negatively correlated estimators. Though the classical method and chain base method are both used for time series decomposition, the chain base method is recommended when a case of multicollinearity has been established.

References

F. Anna, and H. D. Acquah, (2011) A regional analysis of corn yield models:comparing quadratic versus cubic trends, Journal of

Economics and Behavioral Studies, vol. 3, no. 6, pp. 395–401, 2011.

R. B. Bacastow, C. D. Keeping, and T. P. Whorf, Seasonal amplitude increase in atmospheric Co2concentration at Mauna Loa, Hawaii, 1959-1982, Journal of Geophysical Research, vol. 90, issue D6, pp. 10529-10540, 1985.

C. Chatfield, The analysis of time series :theory and practice, John Wiley and Sons, New York, 1975.

S. Chatterjee, and A. G. Greenwood, Note on second-order polynomial regression models, Decision Sciences, vol. 21, issue 1, pp.241-245, 1990.

W. S. Cleveland, A. E. Freeny and T. E. Graedel, The seasonal component of atmospheric Co2: Infomation from new approaches to

the decomposition of seasonal time series, Journal of GeophysicalResearch, vol. 88, issue C15, pp. 10934–10946, 1983.

S. A. DeLurgio, Forecasting principles and applications, Irwin McGraw-Hill, New York, 1998.

N. R. Draper, and H. Smith, Applied regression analysis, 2nd edn,

John Wiley and Sons, New York, 1981.

M. C. Fabrizio, J. Raz and R. R. Bandeker, Using linear models with correlated errors to analyze changes in abundance of lake Michigan fishes:1973-1992 Canadian Journal of Fisheries and Aquatic Sciences, vol. 57, no. 4, pp. 775-788, 2000.

C. Frankze Nonlinear trends, long range dependence and climate noise properties of surface temperature, Journal of Climate, vol. 25, issue 12, pp. 4172-4183, 2012.

J. D. Hamilton, Time series analysis, Princeton University Press, New Jersey, 1994.

B. R. Hargreaves, and T. P. McWilliams Polynomial trend line function flaws in microsoft excel, Computational Statistics and Data Analysis, vol. 54, issue 4, pp. 1190-1196, 2010.

I. S. Iwueze , and E. C. Nwogu , Buys-Ballot estimates for time series decomposition, Global Journal of Mathematical Sciences, vol. 3, no. 2, pp. 83-89, 2004.

I. S. Iwueze, and E. C Nwogu, Buys-Ballot for exponential and s-shaped curves, for time series, Journal of Nigerian Association of Mathematical Physics, vol. 9, pp. 357-366, 2005.

I. S. Iwueze, and E. C. Nwogu, Framework for choice of models and detection of seasonal effect in time series Far East Journal of Theoretical Statistics, vol. 48, issue 1, pp. 45-66, 2014.

I. S. Iwueze, E. C. Nwogu, and J. C. Ajaraogu, Properties of Buys-Ballot estimates when the trend-cycle component of a time series is linear:Additive case, International Journal of Mathematics and Computation, vol. 8, no. 10, pp. 59-77, 2010.

I. S. Iwueze, E. C. Nwogu, and J. C. Ajaraogu, Best linear Unbiased estimate using Buys-Ballot procedure when the trend-cycle component of a time series is linear, Pakistan Journal of Statistics and Operation Research, vol. 7, no. 2, pp. 183-198, 2011.

I. S. Iwueze, and J. Ohakwe(2004) Buys-Ballot estimates when stochastic trend is quadratic. Journal of Nigerian Association of Mathematical Physics, vol. 8, pp. 311-318, 2004.

A. T. Jebb, L. Tay, W. Wang, and Q. Huang Q, Time series analysis for psychological research:examining and forecasting change, Frontiers in Psychology, vol. 6, article 727, pp. 1-24, 2015.

L. Michael, and D. Makowski, Comparison of statistical models for analyzing wheat yield time series, Plos One, vol. 8, issue 10, pp. 1-11, 2013.

I. C. Ndong, M. V. Reenen, D. A. Boakye, W. F. Mbacham, and A. F. Grobler, Trends in malaria admissions at the Mbakong Health Centre of the worth West region of Cameroon: a retrospective study, Malaria Journal, vol. 13, issue 1, pp. 328-339, 2014.

U. C. Nduka, S. I. Iwueze, and E. C. Nwogu, Fitting polynomial trend to time series by method of Buys-Ballot estimators, Communications in Statistics- Theory and Methods, vol. 46, issue 9, pp. 4520-4538, 2017.

E. C. Nwogu, I. S. Iwueze, and V. U. Nlebedim Some tests for seasonality in time series data, Journal of Modern Applied Statistical Methods, vol. 15, issue 2, pp. 382-399, 2016.

O. E. Okereke, I. S. Iwueze, and J. Ohakwe, Necessary conditions for the application of moving average process of order three, Applied Mathematics, vol. 6, pp. 173-181, 2015.

M. Schacam,and N. Brauner, Minimizing the effects of collinearity in polynomial regression, Industrial and Engineering Chemistry Research, vol. 36, issue 10, pp. 4405-4412, 1997.

B. Snook, B. Doan, and R. M. Cullen Publication and research trends in police psychology:A review of five forensic psychology journals, Journal of Police and Criminal Psychology, vol. 24, pp. 45-50, 2009.

Time series analysis, www.wright.edu/haddeus.tarpey/ES714timeseries.pdf.

Published
2018-06-24
How to Cite
Okereke, E. (2018). Buys-Ballot Technique for the Analysis of Time Series with a Cubic-Trend Component. Statistics, Optimization & Information Computing, 6(2), 248-265. https://doi.org/10.19139/soic.v6i2.294
Section
Research Articles