Extending Linear Model With R

Linear models are central to the practice of statistics. They are part of the core knowledge expected of any applied statistician. Linear models are the foundation of a broad range of statistical methodologies; this book is a survey of techniques that grow from a linear model. Our starting point is the regression model with response y and predictors x1, , xp. The model takes the form: y=â0+â1x1+, +âpxp+å where å is normally distributed. This book presents three extensions to this framework. The first generalizes the y part; the second, the å part; and the third, the x part of the linear model.