Robust statistical methods with R

✍ Scribed by Jurečková, Jana; Picek, Jan; Schindler, Martin

Publisher: CRC Press
Year: 2019
Tongue: English
Leaves: 269
Edition: Second edition
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust procedures in measurement Read more...

Abstract: The second edition of Robust Statistical Methods with R provides a systematic treatment of robust procedures with an emphasis on new developments and on the computational aspects. There are many numerical examples and notes on the R environment, and the updated chapter on the multivariate model contains additional material on visualization of multivariate data in R. A new chapter on robust procedures in measurement error models concentrates mainly on the rank procedures, less sensitive to errors than other procedures. This book will be an invaluable resource for researchers and postgraduate students in statistics and mathematics

✦ Table of Contents

Content: Introduction --
Mathematical tools of robustness --
Characteristics of robustness --
Estimation of real parameter --
Linear model --
Multivariate model --
Large sample and finite sample behavior of robust estimators --
Robust and nonparametric procedures in measurement error models --
Appendix A.

✦ Subjects

Robust statistics.;Mathematical statistics.;R (Computer program language)

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