# Robust Nonparametric Statistical Methods

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Dezember 2010

## Beschreibung

### Inhaltsverzeichnis

One-Sample Problems IntroductionLocation Model

Geometry and Inference in the Location Model

Examples

Properties of Norm-Based Inference Robustness Properties of Norm-Based Inference

Inference and the Wilcoxon Signed-Rank Norm

Inference Based on General Signed-Rank Norms

Ranked Set Sampling

L1 Interpolated Confidence Intervals

Two-Sample Analysis

Two-Sample Problems Introduction

Geometric Motivation Examples

Inference Based on the Mann-Whitney-Wilcoxon General Rank Scores

L1 Analyses

Robustness Properties

Proportional Hazards

Two-Sample Rank Set Sampling (RSS)

Two-Sample Scale Problem

Behrens-Fisher Problem

Paired Designs

Linear Models

Introduction

Geometry of Estimation and Tests

Examples

Assumptions for Asymptotic Theory

Theory of Rank-Based Estimates Theory of Rank-Based Tests Implementation of the R Analysis

L1 Analysis

Diagnostics

Survival Analysis

Correlation Model

High Breakdown (HBR) Estimates Diagnostics for Differentiating between Fits

Rank-Based Procedures for Nonlinear Models

Experimental Designs: Fixed Effects Introduction

One-Way Design Multiple Comparison Procedures

Two-Way Crossed Factorial

Analysis of Covariance

Further Examples

Rank Transform

Models with Dependent Error Structure

Introduction

General Mixed Models

Simple Mixed Models Arnold Transformations

General Estimating Equations (GEE)

Time Series

Multivariate Multivariate Location Model

Componentwise

Spatial Methods

Affine Equivariant and Invariant Methods

Robustness of Estimates of Location

Linear Model

Experimental Designs

Appendix: Asymptotic Results

References

Index

### Portrait

Thomas P. Hettmansperger is a professor emeritus of statistics at Penn State University. Dr. Hettmansperger is a fellow of the American Statistical Association and Institute of Mathematical Statistics and an elected member of the International Statistical Institute. His research interests span nonparametric statistics, robust methods, and mixture models. Joseph W. McKean is a professor of statistics at Western Michigan University. His research interests include robust nonparametric procedures for linear, nonlinear, and mixed models and times series designs. A fellow of the American Statistical Association, Dr. McKean has developed highly efficient and high breakdown procedures.### Pressestimmen

The coverage is expanded over the first edition to include recent developments in the field. ... Hettmansperger and McKean examine a wealth of interesting problems in connection with applying nonparametric robust methods. ... this is a well-written and nicely presented book that is likely to appeal to a reader with a good mathematical background and an interest in robust and nonparametric statistical methods. In my opinion, the book could provide the basis for a seminar in robust non-parametric methods for graduate students in statistics or mathematics. -Eugenia Stoimenova, Journal of Applied Statistics, June 2012 ... more logical and concise and more user-friendly ... the book will be equally attractive to instructors, students, and researchers. In summary, this is a well written, structured, and presented book and offers readers plenty of examples and exercises. If I have the opportunity in the near future to offer a graduate course on robust nonparametric methods, I will definitely adopt this book with no hesitation. -Technometrics, November 2011 This book gives an excellent treatment of modern rank-based methods with a special attention to their practical application to data. ... a welcome highly up-to-date and very readable contribution to the field. It will certainly become a standard reference for nonparametric and robust methods. I recommend the book as an important textbook for research libraries. The book will soon find its place on the shelves and the tables of many kind of researchers and will serve as a graduate course textbook. -Hannu Oja, International Statistical Review (2011), 79 ... a fine capstone course in non-parametric statistics. -MAA Reviews, June 2011EAN: 9781439809082

ISBN: 1439809089

Untertitel: Sprache: Englisch.

Verlag: CRC PR INC

Erscheinungsdatum: Dezember 2010

Seitenanzahl: 535 Seiten

Format: gebunden

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