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Generalized Additive Models

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Generalized Additive Models Synopsis

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.

About This Edition

ISBN: 9780412343902
Publication date:
Author: Trevor Hastie, R J Tibshirani
Publisher: Chapman & Hall/CRC an imprint of CRC Press
Format: Hardback
Pagination: 335 pages
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Genres: Probability and statistics

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