This paper extensively investigates the theory of estimating the regression coefficient matrix for the normal GNANOVA model. We explicitly construct estimators which improve the maximum likehood estimator under an invariant scalar loss function. These include the double shrinkage estimators and...

In the GMANOVA model or equivalentry growth curve model, shrinkage effects on the MLE are considered under an invariant risk matrix. We first study the fundamental structure of the problem through which we decompose the estimation problem into some conditional problems and then demonstrate some...

In a balanced one-way model with random effects, the simultaneous estimation of the variance components are considered under the intrinsic Kullback-Leibler loss function. The uniformly minimum variance unbiased (UMVU) or ANOVA estimators are known to have a drawback of taking negative values....

Suppose that one can observe bivariate random variables (L,X) only when L≤X holds. Such data are called left-truncated data and found in many fields, such as experimental education and epidemiology. Recently, a method of fitting a parametric model on (L,X) has been considered, which can easily...

Many statistical methods for truncated data rely on the independence assumption regarding the truncation variable. In many application studies, however, the dependence between a variable X of interest and its truncation variable L plays a fundamental role in modeling data structure. For...

Lattice conditional independence (LCI) models introduced by S. A. Andersson and M. D. Perlman (1993, Ann. Statist.21, 1318-1358) have the pleasant feature of admitting explicit maximum likelihood estimators and likelihood ratio test statistics. This is because the likelihood function and...