Robust diagnostic regression analysis

This book is about using graphs to understand the relationship between a regression model and the data to which it is fitted. Because of the new way in which models are fitted, for example by least squares, we can lose information about the effect of individual observations on inferences about the form and parameters of the model. The methods developed in this book reveal how the fitted regression model depends on individual observations and on groups of observations. Robust procedures can sometimes reveal this structure, but downweight or discard some observations. The novelty in this book is to combine robustness and a "forward" search through the data with regression diagnostics and computer graphics.

Some Regression Examples.- Regression and the Forward Search.- Regression.- Transformations to Normality.- Nonlinear Least Squares.- Generalized Linear Models

Acceso de usuarios registrados

¿Es nuevo? Regístrese

Coordinado por: