Robust Multivariate Analysis - Rilegato

Olive, David

 
9783319682518: Robust Multivariate Analysis
Rilegato
ISBN 10: 3319682512 ISBN 13: 9783319682518
Casa editrice: Springer Verlag, 2017

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull'autore

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.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer Verlag
Data di pubblicazione
2017
Lingua
Inglese
ISBN 10 
3319682512
ISBN 13 
9783319682518
Rilegatura
Copertina rigida
Numero edizione
1
Numero di pagine
520
Contatto del produttore
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Germania

Altre edizioni note dello stesso titolo

9783319885711: Robust Multivariate Analysis

Edizione in evidenza

ISBN 10:  3319885715 ISBN 13:  9783319885711
Casa editrice: Springer Nature, 2018
Brossura