Robust Statistical Procedures

This book PDF is perfect for those who love Mathematics genre, written by Peter J. Huber and published by SIAM which was released on 01 January 1996 with total hardcover pages 77. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Robust Statistical Procedures books below.

Robust Statistical Procedures

Author	: Peter J. Huber
File Size	: 52,8 Mb
Publisher	: SIAM
Language	: English
Release Date	: 01 January 1996
ISBN	: 1611970032
Pages	: 77 pages

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Robust Statistical Procedures by Peter J. Huber Book PDF Summary

Here is a brief, well-organized, and easy-to-follow introduction and overview of robust statistics. Huber focuses primarily on the important and clearly understood case of distribution robustness, where the shape of the true underlying distribution deviates slightly from the assumed model (usually the Gaussian law). An additional chapter on recent developments in robustness has been added and the reference list has been expanded and updated from the 1977 edition.

Robust Statistical Procedures by Peter J. Huber

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Robust Statistical Procedures by Jana Jurecková,Pranab Kumar Sen

A broad and unified methodology for robust statistics—with exciting new applications Robust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the more diverse and sometimes confounding areas, given the many different assessments and interpretations of robustness by theoretical and applied statisticians.

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Robust Statistics by Ricardo A. Maronna,R. Douglas Martin,Victor J. Yohai,Matías Salibián-Barrera

A new edition of this popular text on robust statistics, thoroughly updated to include new and improved methods and focus on implementation of methodology using the increasingly popular open-source software R. Classical statistics fail to cope well with outliers associated with deviations from standard distributions. Robust statistical methods take into

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Robust Statistical Methods with R Second Edition by Jana Jurečková,Jan Picek,Martin Schindler

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

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Robust Statistical Procedures by Jana Jurečková

Download or read online Robust Statistical Procedures written by Jana Jurečková, published by Unknown which was released on 1996. Get Robust Statistical Procedures Books now! Available in PDF, ePub and Kindle.

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Robust Nonparametric Statistical Methods by Thomas P. Hettmansperger,Joseph W. McKean

Offering an alternative to traditional statistical procedures which are based on least squares fitting, the authors cover such topics as one and two sample location models, linear models, and multivariate models. Both theory and applications are examined.

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Robust Statistical Methods with R by Jana Jureckova,Jan Picek

Robust statistical methods were developed to supplement the classical procedures when the data violate classical assumptions. They are ideally suited to applied research across a broad spectrum of study, yet most books on the subject are narrowly focused, overly theoretical, or simply outdated. Robust Statistical Methods with R provides a

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Robust Statistics by Ricardo A. Maronna,Douglas R. Martin,Victor J. Yohai

Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and different applications considered.

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