An edition of Adaptive regression (2000)

Adaptive Regression

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Last edited by MARC Bot
September 28, 2024 | History
An edition of Adaptive regression (2000)

Adaptive Regression

  • 2 Want to read

"Since 1757, when Roger Joseph Boscovich addressed the fundamental mathematical problem in determining the parameters which best fits observational equations, a large number of estimation methods has been proposed and developed for linear regression. Four of the commonly used methods are the least absolute deviations, least squares, trimmed least squares, and the M-regression. Each of these methods has its own competitive edge but none is good for all purposes.

This book focuses on construction of an adaptive combination of several pairs of these estimation methods. The purpose of adaptive methods is to help users make an objective choice and combine desirable properties of two estimators.".

"With this single objective in mind, this book describes in detail the theory, method, and algorithm for combining several pairs of estimation methods. It will be of interest for those who wish to perform regression analyses beyond the least squares method, and for researchers in robust statistics and graduate students who wish to learn some asymptotic theory for linear models.".

"The methods presented in this book are illustrated on numerical examples based on real data. The computer programs in S-PLUS for all procedures presented are available for data analysts working with applications in industry, economics, and the experimental sciences."--BOOK JACKET.

Publish Date
Publisher
Springer
Language
English
Pages
177

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Edition Availability
Cover of: Adaptive Regression
Adaptive Regression
2012, Springer London, Limited
in English
Cover of: Adaptive Regression
Adaptive Regression
2012, Springer New York
in English
Cover of: Adaptive Regression
Adaptive Regression
April 20, 2000, Springer
in English

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Book Details


Classifications

Library of Congress
QA276-280QA276-280QA, QA278.2 .D64 2000

ID Numbers

Open Library
OL7449899M
ISBN 10
038798965X
ISBN 13
9780387989655
LCCN
99055979
OCLC/WorldCat
42753412
Library Thing
2575394
Goodreads
4981754

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September 28, 2024 Edited by MARC Bot import existing book
July 9, 2024 Edited by MARC Bot import existing book
February 11, 2019 Created by MARC Bot import existing book