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Introduction to Robust Estimation and Hypothesis Testing, 3rd Edition

Introduction to Robust Estimation and Hypothesis Testing, 3rd Edition

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Contents

Table of Contents

Introduction to Robust Estimation and Hypothesis Testing

Table of Contents

2 A Foundation for Robust Methods

3 Estimating Measures of Location and Scale

3.1 A Bootstrap Estimate of a Standard Error

3.2 Density Estimators

3.3 The Sample Trimmed Mean

3.3.1 R Functions mean, tmean, and lloc

3.3.2 Estimating the Standard Error of the Trimmed Mean

3.3.3 Estimating the Standard Error of the Sample Winsorized Mean

3.3.4 R Functions winmean, winvar, trimse, and winse

3.3.5 Estimating the Standard Error of the Sample Median, M

3.3.6 R Function msmedse

3.4 The Finite Sample Breakdown Point

3.5 Estimating Quantiles

3.6 An M-Estimator of Location

3.7 One-Step M-estimator

3.8 W-estimators

3.9 The Hodges-Lehmann Estimator

3.10 Skipped Estimators

3.11 Some Comparisons of the Location Estimators

3.12 More Measures of Scale

3.13 Some Outlier Detection Methods

4 Confidence Intervals in the One-Sample Case

5 Comparing Two Groups

6 Some Multivariate Methods

7 One-Way and Higher Designs for Independent Groups

8 Comparing Multiple Dependent Groups

9 Correlation and Tests of Independence

10 Robust Regression

11 More Regression Methods

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