Inference for threshold models with variance components from the generalized linear mixed model perspective

In this paper, the Gibbs sampler, a numerical procedure for generating marginal distri- butions from conditional distributions, is employed to obtain marginal

A marginal quasi-likelihood approach to the analysis of Poisson variables with generalized linear mixed

For the non-independent multivariate gamma models, it is then pointed out that the UMVU and the maxi- mum likelihood estimators are not proportional as conjectured for models

The problem of handling missing data in generalized linear mixed models with correlated covariates is considered when the missing mechanism con- cerns both the response variable and

In addition to handling the relationship between observed data and the latent trait via the link and distribution functions, any system for expected and observed scale quantitative

We have presented a new procedure, SFDS, for the problem of learning linear models with unknown noise level under the fused sparsity scenario.. We showed that this procedure is

In this article, we show that for nonlinear mixed effects models with Gaussian random effects, Expectation Maximization (EM) like algorithms for the computation of the

In the presence of small deviations from the model (Figure 2), the χ 2 approximation of the classical test is extremely inaccurate (even for n = 100), its saddlepoint version and