Handbook of Statistics 15: Robust Inference (Handbok of Statistics, Vol. 15) (Handbok of Statistics, Vol. 15)

Hardbound. This reference work covers the many aspects of Robust Inference. Much of what is contained in the chapters, written by leading experts in the field, has not been part of previous surveys of this area. Robust Inference has been an active area of research for the last two decades. Especially during recent years it has been extended in different directions covering a wide variety of models. This volume will be valuable for both graduate students and researchers using statistical methods. Handbook of Statistics 15: Robust Inference......Page 1 Table of Contents......Page 3 Preface......Page 11 1. Robust Inference in Multivariate Linear Regression Using Difference of Two Convex Functions as the Discrepancy Measure......Page 16 2. Minimum Distance Estimation: The Approach Using Density-based Distances......Page 35 3. Robust Inference: The Approach Based on Influence Functions......Page 63 4. Practical Applications of Bounded-Influence Tests......Page 90 5. Introduction to Positive-Breakdown Methods......Page 114 6. Outlier Identification and Robust Methods......Page 135 7. Rank-Based Analyses of Linear Models......Page 156 8. Rank Tests for Linear Models......Page 185 9. Some Extensions in the Robust Estimation of Parameters of Exponential and Double Exponential Distributions in the Presence of Multiple Outliers......Page 210 10. Outliers, Unit Roots and Robust Estimation of Nonstationary Time Series......Page 245 11. Autocorrelation-Robust Inference......Page 275 12. A Practitioner's Guide to Robust Covariance Matrix Estimation......Page 307 13. Approaches to the Robust Estimation of Mixed Models......Page 351 14. Nonparametric Maximum Likelihood Methods......Page 393 15. A Guide to Censored Quantile Regressions......Page 413 16. What Can Be Learned about Population Parameters when the Data Are Contaminated......Page 446 17. Asymptotic Representations and Interrelations of Robust Estimators and Their Applications......Page 474 18. Small Sample Asymptotics: Applications in Robustness......Page 520 19. On the Fundamentals of Data Robustness......Page 544 20. Statistical Analysis with Incomplete Data: A Selective Review......Page 557 21. Contamination Level and Sensitivity of Robust Tests......Page 639 22. Finite Sample Robustness of Tests: An Overview......Page 650 23. Future Directions......Page 666 Subject Index......Page 681 Handbook of Statistics: Contents of Previous Volumes......Page 687 Consider a general multivariate regression model Yi = X1i + Ei, i = 1, 2, . . . , n (1.1) where Yi is p-vector of observations, Xi's are m x p given matrices, is an m-vector of unknown parameters, and Ei is a p-vector of unobservable random error suitably centered and having a p-variate distribution. This handbook brings together papers on several aspects of robust inference. Many of the areas included have not been covered in previous surveys in this area. Edited By G.s. Maddala, C.r. Rao. Includes Bibliographical References And Index.