Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing

Fourth edition

Hardback (23 Sep 2016)

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Publisher's Synopsis

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon, is a 'how-to' on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that can provide substantial gains in power as well as a deeper, more accurate and more nuanced understanding of data. Since the last edition, there have been numerous advances and improvements. They include new techniques for comparing groups and measuring effect size as well as new methods for comparing quantiles. Many new regression methods have been added that include both parametric and nonparametric techniques. The methods related to ANCOVA have been expanded considerably. New perspectives related to discrete distributions with a relatively small sample space are described as well as new results relevant to the shift function. The practical importance of these methods is illustrated using data from real world studies. The R package written for this book now contains over 1200 functions.

New to this edition

  • 35% revised content
  • Covers many new and improved R functions
  • New techniques that deal with a wide range of situations

Book information

ISBN: 9780128047330
Publisher: Elsevier Science
Imprint: Academic Press
Pub date:
Edition: Fourth edition
DEWEY: 519.544
DEWEY edition: 23
Language: English
Number of pages: 810
Weight: 1752g
Height: 244mm
Width: 202mm
Spine width: 47mm