David J. Olive

Robust Multivariate Analysis (eBook, PDF)

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 501
• Erscheinungstermin: 28. November 2017
• Englisch
• ISBN-13: 9783319682532
• Artikelnr.: 53064021

Autorenporträt

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.

Inhaltsangabe

Introduction.- Multivariate Distributions.- Elliptically Contoured Distributions.- MLD Estimators.- DD Plots and Prediction Regions.- Principal Component Analysis.- Canonical Correlation Analysis.- Discrimination Analysis.- Hotelling's T^2 Test.- MANOVA.- Factor Analysis.- Multivariate Linear Regression.- Clustering.- Other Techniques.- Stuff for Students.

Rezensionen

"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)