Generalized linear mixed models (GLMM) are useful in a variety of applications. With surrogate covariate data, existing methods of inference for GLMM are usually computationally intensive. We propose ...
Mixed linear models are used to analyze data in many settings. These models have a multivariate normal formulation in most cases. The maximum likelihood estimator (MLE) or the residual MLE (REML) is ...
Limitations of linear regression applied on ecological data -- Things are not always linear : additive modeling -- Dealing with heterogeneity -- Mixed effects modeling for nested data -- Violation of ...
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