Mathematical Statistics
Basic Ideas and Selected Topics, Volume II
1st Edition
Published on 4. November 2015
485 pages
978-1-4987-2271-1 (ISBN)
Description
Mathematical Statistics: Basic Ideas and Selected Topics, Volume II presents important statistical concepts, methods, and tools not covered in the authors' previous volume. This second volume focuses on inference in non- and semiparametric models. It not only reexamines the procedures introduced in the first volume from a more sophisticated point o
Reviews / Votes
" . . . the authors have done a superb job of selecting topics comprising most of the essential knowledge needed formodern research. Furthermore, these modern topics are considered with greater depth and sophistication than is usual in a general purpose text. And throughout its pages the book does a good job of linking the mathematical developments to major examples. The choice of topics and examples, along with the depth of coverage are the most attractive features of this volume."~RobertW. Keener, University of Michigan
More details
Series
Edition
1. Auflage
Language
English
Place of publication
Philadelphia, PA
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Product notice
Reflowable
Illustrations
1 s/w Abbildung
1 b/w image
ISBN-13
978-1-4987-2271-1 (9781498722711)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Book
11/2015
1st Edition
Chapman & Hall/CRC
€120.50
Shipment within 15-20 days
Persons
Peter J. Bickel is a professor emeritus in the Department of Statistics and a professor in the Graduate School at the University of California, Berkeley. Dr. Bickel is a member of the American Academy of Arts and Sciences and the National Academy of Sciences. He has been a Guggenheim Fellow and MacArthur Fellow, a recipient of the COPSS Presidents' Award, and president of the Bernoulli Society and the Institute of Mathematical Statistics. He holds honorary doctorate degrees from the Hebrew University of Jerusalem and ETH Zurich.
Kjell A. Doksum is a senior scientist in the Department of Statistics at the University of Wisconsin-Madison. His research encompasses the estimation of nonparametric regression and correlation curves, inference for global measures of association in semiparametric and nonparametric settings, the estimation of regression quantiles, statistical modeling and analysis of HIV data, the analysis of financial data, and Bayesian nonparametric inference.
Kjell A. Doksum is a senior scientist in the Department of Statistics at the University of Wisconsin-Madison. His research encompasses the estimation of nonparametric regression and correlation curves, inference for global measures of association in semiparametric and nonparametric settings, the estimation of regression quantiles, statistical modeling and analysis of HIV data, the analysis of financial data, and Bayesian nonparametric inference.
Content
Introduction and Examples. Tools for Asymptotic Analysis. Distribution-Free, Unbiased, and Equivariant Procedures. Inference in Semiparametric Models. Monte Carlo Methods. Nonparametric Inference for Functions of One Variable. Prediction and Machine Learning. Appendices. References. Indices.
