Statistical Learning from a Regression Perspective
This textbook considers statistical learning applications when interest centers on the conditional distribution of a response variable, given a set of predictors, and in the absence of a credible model that can be specified before the data analysis begins
- PDF / 13,270,343 Bytes
- 451 Pages / 439.42 x 683.15 pts Page_size
- 79 Downloads / 226 Views
Richard A. Berk
Statistical Learning from a Regression Perspective Third Edition
Springer Texts in Statistics Series Editors G. Allen, Department of Statistics, Houston, TX, USA R. De Veaux, Department of Mathematics and Statistics, Williams College, Williamstown, MA, USA R. Nugent, Department of Statistics, Carnegie Mellon University, Pittsburgh, PA, USA
Springer Texts in Statistics (STS) includes advanced textbooks from 3rd- to 4th-year undergraduate courses to 1st- to 2nd-year graduate courses. Exercise sets should be included. The series editors are currently Genevera I. Allen, Richard D. De Veaux, and Rebecca Nugent. Stephen Fienberg, George Casella, and Ingram Olkin were editors of the series for many years.
More information about this series at http://www.springer.com/series/417
Richard A. Berk
Statistical Learning from a Regression Perspective Third Edition
Richard A. Berk Department of Criminology Schools of Arts and Sciences University of Pennsylvania Philadelphia, PA, USA
ISSN 1431-875X ISSN 2197-4136 (electronic) Springer Texts in Statistics ISBN 978-3-030-40188-7 ISBN 978-3-030-40189-4 (eBook) https://doi.org/10.1007/978-3-030-40189-4 © Springer Nature Switzerland AG 2008, 2016, 2020 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, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
In God we trust. All others must have data (W. Edwards Deming)
In memory of Peter H. Rossi, a mentor, colleague, and friend
Preface to the Third Edition
The preface to the third edition is very brief. There is substantial continuity with the Second Edition in aims, conventions, and style. But there are also some important differences. First, there have been useful theoretical advances and ways to rethink statistical inference for st
Data Loading...
