9780367403379-0367403374-Transformation and Weighting in Regression (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Transformation and Weighting in Regression (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

ISBN-13: 9780367403379
ISBN-10: 0367403374
Edition: 1
Author: David Ruppert, Raymond J. Carroll
Publication date: 2019
Publisher: Chapman and Hall/CRC
Format: Paperback 264 pages
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Book details

ISBN-13: 9780367403379
ISBN-10: 0367403374
Edition: 1
Author: David Ruppert, Raymond J. Carroll
Publication date: 2019
Publisher: Chapman and Hall/CRC
Format: Paperback 264 pages

Summary

Transformation and Weighting in Regression (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) (ISBN-13: 9780367403379 and ISBN-10: 0367403374), written by authors David Ruppert, Raymond J. Carroll, was published by Chapman and Hall/CRC in 2019. With an overall rating of 4.2 stars, it's a notable title among other books. You can easily purchase or rent Transformation and Weighting in Regression (Chapman & Hall/CRC Monographs on Statistics and Applied Probability) (Paperback) from BooksRun, along with many other new and used books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.5.

Description

This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research.

While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

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