Premium
Theory & Methods: Bayesian estimates in a one‐way ANOVA random effects model
Author(s) -
Bian Guorui
Publication year - 2002
Publication title -
australian and new zealand journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 41
eISSN - 1467-842X
pISSN - 1369-1473
DOI - 10.1111/1467-842x.00211
Subject(s) - estimator , mathematics , statistics , bayesian probability , variance (accounting) , m estimator , bayes estimator , random effects model , extremum estimator , posterior probability , econometrics , medicine , meta analysis , accounting , business
Bayesian estimators of variance components are developed, based on posterior mean and posterior mode, respectively, in a one‐way ANOVA random effects model with independent prior distributions. The formulas for the proposed estimators are simple. The estimators give sensible results for ‘badly‐behaved’ datasets, where the standard unbiased estimates are negative. They are markedly robust as compared to the existing estimators such as the maximum likelihood estimators and the maximum posterior density estimators.