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MIVQUE and REML Estimators of Variance Components under Proportionality Condition
Author(s) -
Hossain Syed Shahadat,
Muttlak H.A.
Publication year - 1998
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/(sici)1521-4036(199811)40:7<845::aid-bimj845>3.0.co;2-c
Subject(s) - restricted maximum likelihood , mathematics , estimator , statistics , variance (accounting) , minimum variance unbiased estimator , best linear unbiased prediction , maximum likelihood , computer science , accounting , business , selection (genetic algorithm) , artificial intelligence
In this study, a one‐way random effect model with unequal cell variances is considered, and the Minimum Variance Quadratic Unbiased Estimator (MIVQUE) and Restricted Maximum Likelihood (REML) estimator of the variance components are studied. The algebraic inversion of the variance matrix of the observation vector is obtained to achieve some computational convenience. Using the proportionality condition described by Talukder (1992) that the cell sizes are proportional to the cell variances, MIVQUE and REML estimators are shown to be the same as the ANOVA estimators.