Robust Nonparametric Statistical Methods

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Dezember 2010



One-Sample Problems Introduction
Location Model
Geometry and Inference in the Location Model
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
Geometry of Estimation and Tests
Assumptions for Asymptotic Theory
Theory of Rank-Based Estimates Theory of Rank-Based Tests Implementation of the R Analysis
L1 Analysis
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
General Mixed Models
Simple Mixed Models Arnold Transformations
General Estimating Equations (GEE)
Time Series

Multivariate Multivariate Location Model
Spatial Methods
Affine Equivariant and Invariant Methods
Robustness of Estimates of Location
Linear Model
Experimental Designs

Appendix: Asymptotic Results




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.


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 2011
EAN: 9781439809082
ISBN: 1439809089
Untertitel: Sprache: Englisch.
Verlag: CRC PR INC
Erscheinungsdatum: Dezember 2010
Seitenanzahl: 535 Seiten
Format: gebunden
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