Regression analysis answers questions about the dependence of a response variable on one or more predictors, including prediction of future values of a response, discovering which predictors are important, and estimating the impact of changing a predictor or a treatment on the value of the response. At the publication of the second edition of this book about 20 years ago, regression analysis using least squares was essentially the only methodology available to analysts interested in questions like these. Cheap, widely available high-speed computing has changed the rules for examining these questions. Modern competitors include nonparametric regression, neural networks, support vector machines, and tree-based methods, among others.
330 pàg
Peso: 4 mb
Idioma:
Edición: 3ra
Autor:
Michael Kutner
Christopher Nachtsheim
John Neter
0 comentarios:
Publicar un comentario