Back to School Savings: Save up to 30% on print books and eBooks. No promo code needed.
Back to School Savings: Save up to 30%
Robustness in Statistics
1st Edition - January 1, 1979
Editors: Robert L. Launer, Graham N. Wilkinson
eBook ISBN:9781483263366
9 7 8 - 1 - 4 8 3 2 - 6 3 3 6 - 6
Robustness in Statistics contains the proceedings of a Workshop on Robustness in Statistics held on April 11-12, 1978, at the Army Research Office in Research Triangle Park, North… Read more
Purchase Options
Save 50% on book bundles
Immediately download your ebook while waiting for your print delivery. No promo code is needed.
Robustness in Statistics contains the proceedings of a Workshop on Robustness in Statistics held on April 11-12, 1978, at the Army Research Office in Research Triangle Park, North Carolina. The papers review the state of the art in statistical robustness and cover topics ranging from robust estimation to the robustness of residual displays and robust smoothing. The application of robust regression to trajectory data reduction is also discussed. Comprised of 14 chapters, this book begins with an introduction to robust estimation, paying particular attention to iteration schemes and error structure of estimators. Sensitivity and influence curves as well as their connection with jackknife estimates are described. The reader is then introduced to a simple analog of trimmed means that can be used for studying residuals from a robust point-of-view; a class of robust estimators (called P-estimators) based on the location and scale-invariant Pitman estimators of location; and robust estimation in the presence of outliers. Subsequent chapters deal with robust regression and its use to reduce trajectory data; tests for censoring of extreme values, especially when population distributions are incompletely defined; and robust estimation for time series autoregressions. This monograph should be of interest to mathematicians and statisticians.
Contributors
Preface
Abstracts of Manuscripts
An Introduction to Robust Estimation
The Robustness of Residual Displays
Robust Smoothing
Robust Pitman-like Estimators
Robust Estimation in the Presence of Outliers
Study of Robustness by Simulation: Particularly Improvement by Adjustment and Combination
Robust Techniques for the User
Application of Robust Regression to Trajectory Data Reduction
Tests for Censoring of Extreme Values (Especially) When Population Distributions Are Incompletely Defined
Robust Estimation for Time Series Autoregressions
Robust Techniques in Communication
Robustness in the Strategy of Scientific Model Building
A Density-Quantile Function Perspective on Robust Estimation