A new procedure for the estimation of variance components
For the estimation of variance components in the one way random effects models, we propose some estimators which avoid negative and zero estimates of the variance component, a well-known problem with customary estimators such as the maximum likelihood or the restricted maximum likelihood estimators. The proposed estimators are shown to have lower mean squared error than the customary estimators over a large range of the parameter space. This is also exhibited in a Monte Carlo study. Extensions of the proposed procedure to more complex situations are also discussed.
restricted maximum likelihood estimators
scientific article; zbMATH DE number 4024549