Linear mixed models (LMMs) are a powerful and established tool for studying genotype–phenotype relationships. A limitation of the LMM is that the model assumes Gaussian distributed residuals, a ...

The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 37, No. 2 (June/juin 2009), pp. 219-234 (16 pages) In many applications of generalized linear mixed models to clustered ...

Generalized linear mixed effects models (GLMM) provide useful tools for correlated and/or over-dispersed non-Gaussian data. This article considers generalized nonparametric mixed effects models (GNMM) ...

Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the response and ...