Vector Generalized Linear and Additive Models With an Implementation
This book presents a statistical framework that expands generalized linear models (GLMs) for regression modelling. The framework shared in this book allows analyses based on many semi-traditional applied statistics models to be performed as a coherent who
- PDF / 10,280,494 Bytes
- 604 Pages / 504.63 x 737.01 pts Page_size
- 49 Downloads / 287 Views
Thomas W. Yee
Vector Generalized Linear and Additive Models With an Implementation in R
Springer Series in Statistics Advisors: P. Bickel, P. Diggle, S.E. Fienberg, U. Gather, I. Olkin, S. Zeger
More information about this series at http://www.springer.com/series/692
Thomas W. Yee
Vector Generalized Linear and Additive Models With an Implementation in R
123
Thomas W. Yee Department of Statistics University of Auckland Auckland, New Zealand
ISSN 0172-7397 ISSN 2197-568X (electronic) Springer Series in Statistics ISBN 978-1-4939-2817-0 ISBN 978-1-4939-2818-7 (eBook) DOI 10.1007/978-1-4939-2818-7 Library of Congress Control Number: 2015945942 Springer New York Heidelberg Dordrecht London © Thomas Yee 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer Science+Business Media LLC New York is part of Springer Science+Business Media (www.springer. com)
To my parents and Selina and Annie
Preface
Beauty will result from the form and correspondence of the whole, with respect to the several parts, of the parts with regard to each other, and of these again to the whole; that the structure may appear an entire and compleat body, wherein each member agrees with the other, and all necessary to compose what you intend to form. —The First Book of Andrea Palladio’s Architecture, 1570
In the early 1970s, the generalized linear model (GLM) class of statistical models was proposed by Nelder and Wedderburn (1972), providing a unified framework for several important regression models. They showed that the linear model, Poisson regression, logistic regression and probit analysis, and others could be treated as special cases of GLMs, and that one algorithm could be used to estimate them all. The unified GLM framework also provides an elegant overriding theoretical structure resulting in inference, diagnostics, software interface, etc. that applies to all of them. Prior to GLMs, these methods were largely treated as unrelated. Since then, GLMs have
Data Loading...
