Minimum Norm Quadratic Estimators of Variance Components.
Minimum variance quadratic unbiased estimation of variance components
Modified minimax quadratic estimation of variance components
The paper deals with modified minimax quadratic estimation of variance and covariance components under full ellipsoidal restrictions. Based on the, so called, linear approach to estimation variance components, i. e. considering useful local transformation of the original model, we can directly adopt the results from the linear theory. Under normality assumption we can can derive the explicit form of the estimator which is formally find to be the Kuks–Olman type estimator.
Monotonicity properties of statistical procedures for an increasing number of observations or a decreasing number of parameters, especially Anova procedures