Robust Estimation and Testing

Robert G. Staudte, Simon J. Sheather

ISBN 10: 0471855472 / ISBN 13: 9780471855477

Published by John Wiley and Sons Inc, US, 1990

About this Item

An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems.

Seller Inventory # LU-9780471855477

Bibliographic Details

• Title: Robust Estimation and Testing
• Publisher: John Wiley and Sons Inc, US
• Publication Date: 1990
• Language: English
• ISBN 10: 0471855472
• ISBN 13: 9780471855477
• Binding: Hardback
• Edition: 1st.
• Condition: New
• Dimensions: 16.05W x 2.29H x 23.7D centimeters 16.05 centimeters width by 2.29 centimeters height by 23.7 centimeters depth
• Weight: 585 grams

About this title

Synopsis

An introduction to the theory and methods of robust statistics, providing students with practical methods for carrying out robust procedures in a variety of statistical contexts and explaining the advantages of these procedures. In addition, the text develops techniques and concepts likely to be useful in the future analysis of new statistical models and procedures. Emphasizing the concepts of breakdown point and influence functon of an estimator, it demonstrates the technique of expressing an estimator as a descriptive measure from which its influence function can be derived and then used to explore the efficiency and robustness properties of the estimator. Mathematical techniques are complemented by computational algorithms and Minitab macros for finding bootstrap and influence function estimates of standard errors of the estimators, robust confidence intervals, robust regression estimates and their standard errors. Includes examples and problems.

About the Author

Robert G. Staudte and Simon J. Sheather are the authors of Robust Estimation and Testing, published by Wiley.