Maximum likelihood estimation of variance components
Abstract
In this thesis, the Maximum Likelihood and Restricted Maximum Likelihood methods
of estimating variance components are investigated for the one-way model.
Expressions for the estimators and their variances are obtained, and algorithms for
finding the estimates are tested by means of a Monte Carlo study. The quantitative
effects of non-normality on the variability of estimates are discussed. Finally,
diagnostic tests for identifying outliers and non-normality are proposed, and illustrated
with data concerning soybean plant growth.
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