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Robust Regression

Analysis and Applications

Kenneth D. Lawrence Jeffrey L. Arthur

$96.99

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English
CRC Press
30 June 2020
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
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Edited by:  
Imprint:   CRC Press
Country of Publication:   United Kingdom
Dimensions:   Height: 229mm,  Width: 152mm, 
Weight:   453g
ISBN:   9780367580186
ISBN 10:   0367580187
Series:   Statistics: A Series of Textbooks and Monographs
Pages:   310
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

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.

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