Robust Multivariate Analysis - Hardcover

J. Olive, David

 
9783319682518: Robust Multivariate Analysis
Hardcover
ISBN 10: 3319682512 ISBN 13: 9783319682518
Verlag: Springer, 2017

Inhaltsangabe

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. 

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Über die Autorin bzw. den Autor

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. 

Von der hinteren Coverseite

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 multivariatetopics, 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.  

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Verlag
Springer
Erscheinungsdatum
2017
Sprache
Englisch
ISBN 10 
3319682512
ISBN 13 
9783319682518
Einband
Gebundene Ausgabe
Auflage
1
Anzahl der Seiten
517
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland

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9783319885711: Robust Multivariate Analysis

Vorgestellte Ausgabe

ISBN 10:  3319885715 ISBN 13:  9783319885711
Verlag: Springer, 2018
Softcover