Estimating variance components in linear models

AbstractEstimation of variance components in linear model theory is presented as an application of estimation of the mean by introducing a dispersion-mean correspondence. Without any further computations, this yields most general representations of minimum variance-minimum bias-invariant quadratic estimates, estimates from MINQUE theory, and Ridge-type estimates of the variance components