
Robust Regression
Analysis and Applications
Kenneth D. Lawrence(Author)
Routledge (Publisher)
1st Edition
Published on 30. June 2020
Book
Paperback/Softback
310 pages
978-0-367-58018-6 (ISBN)
Description
Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weigh. Each observation discusses generalized properties of LP-estimators. It includes an algorithm for identifying outliers using least absolute value criterion, in regression modelling reviews re-descending M-estimators studies Li linear regres
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Professional
Dimensions
Height: 229 mm
Width: 152 mm
Thickness: 17 mm
Weight
452 gr
ISBN-13
978-0-367-58018-6 (9780367580186)
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

E-Book
05/2019
1st Edition
Routledge
€66.99
Available for download

E-Book
05/2019
1st Edition
Routledge
€66.99
Available for download

Book
12/1989
1st Edition
CRC Press
€328.07
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Person
KENNETH D. LAWRENCE is Adjunct Professor of Industrial and Systems Engineering at Rutgers University in Piscataway, New Jersey. His professional employment includes 20 years of experience in technical management positions in strategic planning and operations research with the U.S. Army Munitions Command, Prudential Insurance, Hoffmann-La Roche, AT&T Long Lines, and AT&T. The author or coauthor of several articles and book chapters on regression analysis and forecasting, he is an associate editor of the Journal of Statistical Computation and Simulation. His professional affiliations include the American Statistical Association, Operations Research Society of America, Institute of Industrial Engineers, Institute of Management Sciences, Institute of Decision Sciences, and Institute of Mathematical Statistics. Dr. Lawrence's graduate education includes master's degrees in statistics, operations research, industrial engineering, finance and management, as well as a doctoral degree in applied statistics and operations research from Rutgers University (1978). JEFFREY L. ARTHUR is Associate Professor of Statistics at Oregon State University in Corvallis, where he has taught since 1977. He is the author or coauthor of several articles on the computational issues of optimization problems in statistics. He is a member of the Institute of Management Sciences and Operations Research Society of America. Professor Arthur received the Ph.D. degree (1977) in operations research and industrial engineering from Purdue University.
Content
Part 1 Advances in Robust Regression, Part II Robust Regression Methods, Part III Forecasting and Robust Regression, Index.