Robust Multivariate Analysis

Authors: J. Olive, David

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  • Includes dozens of R functions for making plots and estimators
  • Problems included at the end of every chapter
  • Code available for download on the author's website
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eBook 64,19 €
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  • ISBN 978-3-319-68253-2
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Hardcover 77,99 €
price for Spain (gross)
  • ISBN 978-3-319-68251-8
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Softcover 77,99 €
price for Spain (gross)
  • ISBN 978-3-319-88571-1
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
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About this Textbook

This text presents methods that are robust to the assumption of a multivariate normal distribution or methods that are robust to certain types of outliers. Instead of using exact theory based on the multivariate normal distribution, the simpler and more applicable large sample theory is given.  The text develops among the first practical robust regression and robust multivariate location and dispersion estimators backed by theory.  

The robust techniques  are illustrated for methods such as principal component analysis, canonical correlation analysis, and factor analysis.  A simple way to bootstrap confidence regions is also provided.

Much of the research on robust multivariate analysis in this book is being published for the first time.  The text is suitable for a first course in Multivariate Statistical Analysis or a first course in Robust Statistics.  This graduate text is also useful for people who are familiar with the traditional multivariate topics, but want to know more about handling data sets with outliers. Many R programs and R data sets are available on the author’s website. 

About the authors

David Olive is a Professor at Southern Illinois University, Carbondale, IL, USA.  His research interests include the development of computationally practical robust multivariate location and dispersion estimators, robust multiple linear regression estimators, and resistant dimension reduction estimators. 

Reviews

“This monograph provides a comprehensive introduction to the mathematical theory of framelets and discrete framelet transforms. … This monograph is well-written for a broad readership and very convenient as a textbook for graduate students and as an advanced reference guide for researchers in applied mathematics, physics, and engineering. Doubtless, this work will stimulate further research on framelets.” (Manfred Tasche, zbMATH 1387.42001, 2018)

Table of contents (15 chapters)

Table of contents (15 chapters)

Buy this book

eBook 64,19 €
price for Spain (gross)
  • ISBN 978-3-319-68253-2
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover 77,99 €
price for Spain (gross)
  • ISBN 978-3-319-68251-8
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
  • The final prices may differ from the prices shown due to specifics of VAT rules
Softcover 77,99 €
price for Spain (gross)
  • ISBN 978-3-319-88571-1
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Robust Multivariate Analysis
Authors
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-68253-2
DOI
10.1007/978-3-319-68253-2
Hardcover ISBN
978-3-319-68251-8
Softcover ISBN
978-3-319-88571-1
Edition Number
1
Number of Pages
XVI, 501
Number of Illustrations
70 b/w illustrations, 6 illustrations in colour
Topics