Using Wavelet Estimation of the Weighted Exponential Regression Model (Statistics, Optimization & Information Computing, 2025)
This paper aims to estimate the parameters of the weighted exponential regression model based on the methods of Maximum Likelihood, Jackknife, Wavelet, and Modified Jackknife method by Haar matrix to predict monthly mortality rates for leukemia patients in Iraq. We compared these methods by collecting samples from July 1, 2020, to February 18, 2023. Simulation was also used to generate three random samples with sizes of 8, 16, and 32 to represent the approved data using MATLAB program. The results indicated the following: The Modified Jackknife method by Haar matrix showed the smallest Mean Absolute Percentage Error compared to Maximum Likelihood, Jackknife, and Wavelet methods for the weighted exponential regression model. The results also showed the stability of the Modified Jackknife method by Haar matrix and the Wavelet method, whether by increasing or decreasing the sample size. That is, the specificity of both methods is not affected by the sample size. Regarding the real data results, the mortality rate from leukemia was forecast for eight months, which showed very low mortality rates that were close to zero.