Extending the Linear Model with R

This modern statistics text discusses the extension of the linear model through the regression model. It extensively addresses the generalized linear model, GLM... » 

This modern statistics text discusses the extension of the linear model through the regression model. It extensively addresses the generalized linear model, GLM diagnostics, generalized linear mixed models, trees, and the use of neural networks in the field of statistics. It discusses the regression model in three forms: through the use of dummy variables for qualitative predictors, by allowing transformation of variables as in the Box-Cox transformation, and the use of weights which allow heterogeneous error structures and the exclusion of outliers. R is used throughout the book to aid with computation and model building. «