On Variance Components Estimators in Repeated Measurements Model

Hayder Abbood Kori

doi:10.55529/jecnam.33.28.39

On Variance Components Estimators in Repeated Measurements Model

https://doi.org/10.55529/jecnam.33.28.39

Authors

Hayder Abbood Kori Department of Economics, College of Administration and Economics, Thi-Qar University, Thi-Qar, Iraq

Keywords:

Repeated Measurements Model (RMM), Random Effects, Maximum Likelihood (ML), Maximum Penalized Likelihood (MPL), Fixed Effect.

Abstract

In this article, we focus our study on estimation the variance components in the two methods: the maximum likelihood function and the maximum penalized likelihood function of the repeated measurements model, which contain three random effects as well as random error, comparing between these estimators based on the mean square error , we also studied the bias and variance for each estimator and supported the theoretical side with an applied example to illustrate the results.

Published

2023-04-26

How to Cite

Hayder Abbood Kori. (2023). On Variance Components Estimators in Repeated Measurements Model. Journal of Electronics, Computer Networking and Applied Mathematics , 3(03), 28–39. https://doi.org/10.55529/jecnam.33.28.39