This report extends the technique of testing single variance components with generalized xed{level tests | in situations when nuisance parameters make exact testing impossible | to the more general way of testing hypotheses on linear forms of variance components. An extension of the deenition of a generalized test variable leads to a generalized xed{level test for arbitrary linear hypotheses on...

In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline estimators. We consider three types of estimation methods: (i) as a standard (fixed effect) nonparametric model, (ii) using the mixed model framework with the spline coefficients as random effects and (iii) a Bayesian approach. The volume-of-tube formula is applied for the first two methods and co...

This paper considers identification and estimation of structural interaction effects in a social interaction model. The model allows unobservables in the group structure, which may be correlated with included regressors. We show that both the endogenous and exogenous interaction effects can be identified if there are sufficient variations in group sizes. We consider the estimation of the model ...

The problem of experimental design for the purpose of estimating the fixed effects and the variance components corresponding to random nested factors is a widely applicable problem in industry. Random nested factors arise from quantity designations such as lot or batch and from sampling and measurement procedures. We introduce a new class of designs, called assembled designs, where all the nest...

R estimators based on the joint ranks (JR) of all the residuals have been developed over the last twenty years for fitting linear models with independently distributed errors. In this paper, we extend these estimators to estimating the fixed effects in a linear model with cluster correlated continuous error distributions for general score functions. We discuss the asymptotic theory of the estim...

In this paper, we consider the problem of selecting the variables of the fixed effects in the linear mixed models where the random effects are present and the observation vectors have been obtained frommany clusters. As the variable selection procedure, we here use the Akaike Information Criterion, AIC. In the context of the mixed linear models, two kinds of AIC have been proposed: marginal AIC...

A nonlinear mixed-effects modeling approach was used to model the individual tree height–diameter relationship based on Chapman-Richards function for dahurian larch (Larix gmelinii. Rupr.) plantations in northeastern China. The study involved the estimation of fixed and random parameters, as well as procedures for determining random effects variance-covariance matrices to reduce the number of t...