On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler

This paper tackles the estimation of parameters of linear mixed random effect one–classification model by Bayesian technique which includes Gibbs sampling. Gibbs sampling is a special case of Monte Carlo Method which uses Markov Chain and so called MCMC (Markov Chain Monte Carlo). This MCMC method...

Full description

Bibliographic Details
Format: Article
Language:Arabic
Published: College of Computer Science and Mathematics, University of Mosul 2008-06-01
Series:المجلة العراقية للعلوم الاحصائية
Online Access:https://stats.mosuljournals.com/article_31516_5152bf6b1c7a1c524e475447d072d062.pdf
_version_ 1811226320404742144
collection DOAJ
description This paper tackles the estimation of parameters of linear mixed random effect one–classification model by Bayesian technique which includes Gibbs sampling. Gibbs sampling is a special case of Monte Carlo Method which uses Markov Chain and so called MCMC (Markov Chain Monte Carlo). This MCMC method depends on partition of difficult and compound models into simple ones which can be manipulated and easily analyzed, specially for the posterior distribution which are not easy to find their final formulae. In this research the mixed random effect linear one–classification model is proposed on a population of 15 treatments including 15 types of cotton plant. A random sample of 5 types is taken and using the analysis of variance method to test the hypothesis that all the 15 types have equal effect and the estimation of the parameters is obtained Gibbs sampling is also used in order to estimate the parameters and then testing the hypothesis of equal effects of treatments. The results obtained in both ANOVA and Gibbs sampling are nearly the same and encouraging. All algorithms are programmed in this research using WinBUGS program.
first_indexed 2024-04-12T09:22:05Z
format Article
id doaj.art-ef59b86bb7904b49b22b31329efdcb95
institution Directory Open Access Journal
issn 1680-855X
2664-2956
language Arabic
last_indexed 2024-04-12T09:22:05Z
publishDate 2008-06-01
publisher College of Computer Science and Mathematics, University of Mosul
record_format Article
series المجلة العراقية للعلوم الاحصائية
spelling doaj.art-ef59b86bb7904b49b22b31329efdcb952022-12-22T03:38:35ZaraCollege of Computer Science and Mathematics, University of Mosulالمجلة العراقية للعلوم الاحصائية1680-855X2664-29562008-06-0181103410.33899/iqjoss.2008.3151631516On Bayesian Estimation in Mixed Linear Models Using the Gibbs SamplerThis paper tackles the estimation of parameters of linear mixed random effect one–classification model by Bayesian technique which includes Gibbs sampling. Gibbs sampling is a special case of Monte Carlo Method which uses Markov Chain and so called MCMC (Markov Chain Monte Carlo). This MCMC method depends on partition of difficult and compound models into simple ones which can be manipulated and easily analyzed, specially for the posterior distribution which are not easy to find their final formulae. In this research the mixed random effect linear one–classification model is proposed on a population of 15 treatments including 15 types of cotton plant. A random sample of 5 types is taken and using the analysis of variance method to test the hypothesis that all the 15 types have equal effect and the estimation of the parameters is obtained Gibbs sampling is also used in order to estimate the parameters and then testing the hypothesis of equal effects of treatments. The results obtained in both ANOVA and Gibbs sampling are nearly the same and encouraging. All algorithms are programmed in this research using WinBUGS program.https://stats.mosuljournals.com/article_31516_5152bf6b1c7a1c524e475447d072d062.pdf
spellingShingle On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler
المجلة العراقية للعلوم الاحصائية
title On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler
title_full On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler
title_fullStr On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler
title_full_unstemmed On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler
title_short On Bayesian Estimation in Mixed Linear Models Using the Gibbs Sampler
title_sort on bayesian estimation in mixed linear models using the gibbs sampler
url https://stats.mosuljournals.com/article_31516_5152bf6b1c7a1c524e475447d072d062.pdf