"Generalized Linear Models," Tuesday, April 6: The third LISA mini course for the 2010 Spring semester focuses on appropriate model building using generalized linear models. While multiple linear ...

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 ...

Keywords: Statistical analyses. Regression models. Post-earthquake ignitions. Data analyses. California. Ground shaking. Generalized linear mixed models. Goodness-of ...

We express the mean and variance terms in a double-exponential regression model as additive functions of the predictors and use Bayesian variable selection to determine which predictors enter the ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...