This paper derives the corrected conditional Akaike information criteria for generalized linear mixed models by analytic approximation and parametric bootstrap. The sampling variation of both fixed effects and variance component parameter estimators are accommodated in the bias correction term....

In this study, a model identification instrument to determine the variance component structure for generalized linear mixed models (glmms) is developed based on the conditional Akaike information (cai). In particular, an asymptotically unbiased estimator of the cai (denoted as caicc) is derived...

Under flexible distributional assumptions, the adjusted quasi-maximum likelihood (adqml) estimator for mixed regressive, spatial autoregressive model is studied in this paper. The proposed estimation method accommodates the extra uncertainty introduced by the unknown regression coefficients....

Studying unified model averaging estimation for the situation with complicated data structure, we propose a novel weight choice criterion with a very general loss function based on cross-validation, and investigate asymptotic properties of the resulting averaging estimator. Under a unified...

This note studies the existence and uniqueness of quasi-maximum likelihood estimator for mixed regressive, spatial autoregression model with continuously distributed response vector. Under very mild conditions that nrank(Xn)+1 (n is the sample size and Xn is the n×p constant matrix of...

Bivariate time series of counts with excess zeros relative to the Poisson process are common in many bioscience applications. Failure to account for the extra zeros in the analysis may result in biased parameter estimates and misleading inferences. A class of bivariate zero-inflated Poisson...