Open AccessDo Prior Type and Sample Size have Effect on Mixtures of Normal? The Monte Carlo evidence
Author(s) -
Ojo O. Oluwadare,
Enesi O. Lateifat,
Owonipa R. Oluremi
Publication year - 2021
Publication title -
asian journal of probability and statistics
Language(s) - English
Resource type - Journals
ISSN - 2582-0230
DOI - 10.9734/ajpas/2020/v10i430255
Subject(s) - sample size determination , monte carlo method , prior probability , statistics , sample (material) , bayesian probability , regression analysis , econometrics , mathematics , computer science , chemistry , chromatography
Overtime finite mixtures of Normal in regression have gained popularity and also shown to be useful in modelling heterogeneous data. This study examines the effects of prior and sample size in regression mixtures of Normal models with Bayesian approach. Monte Carlo experiment was carried out on the Normal mixtures model in order to examine the strength of priors and also to know the suitable sample size to produce stable results. Results obtained from the experiment indicate that an informative prior gives a reliable estimate than non-informative prior while large sample sizes maybe needed to obtain stable results.