for analytics, and (if not signed in) for advertising. By using LibraryThing you acknowledge that you have
Your use of the site and services is subject to these policies and terms.
This book describes an array of power tools for data analysis that are based on nonparametric regression and smoothing techniques. These methods relax the linear assumption of many standard models and allow analysts to uncover structure in the data that might otherwise have been missed. While McCullagh and Nelder's Generalized Linear Models shows how to extend the usual linear methodology to cover analysis of a range of data types, Generalized Additive Models enhances this methodology even further by incorporating the flexibility of nonparametric regression. Clear prose, exercises in each chapter, and case studies enhance this popular text.
(retrieved from Amazon Thu, 12 Mar 2015 18:24:28 -0400)