Other volumes in the Wiley Series in Probability and Mathematical Statistics The Theory of Linear Models and Multivariate Analysis Steven F. Arnold Presents a detailed, theoretical treatment of models that assume an underlying normal distribution. Considers the univariate linear, generalized linear, repeated measures, random effects, mixed, correlation, multivariate linear and discrimination models. Optimal estimation and testing procedures and simultaneous confidence intervals are derived for each. Emphasizes the similarity of univariate and multivariate models. Uses a co-ordinate free notation in which most of the important statistics are defined as projections on particular subspaces or the lengths of such projections. 1981 Approximation Theorems of Mathematical Statistics Robert J. Serfling This book covers asymptotic distribution theory, consistency properties, and asymptotic relative efficiency approaches. It includes methods of proof and emphasizes the manipulation of probability theorems for statistical use. Besides standard types of statistics such as the empirical distribution function, the sample moments, sample quantiles, maximum likelihood estimates, etc., Serfling treats special classes of statistics: U-statistics, differentiable statistical functions, Mestimates, L-estimates, and R-estimates. A readily accessible text for students in statistics, general mathematics, operations research, and selected engineering fields. 1980 Robust Statistics Peter J. Huber A systematic, book-length treatment of the subject. Begins with a general introduction and the formal mathematical background behind qualitative and quantitative robustness. Stresses concepts. Provides selected numerical algorithms for computing robust estimates, as well as convergence proofs. Tables contain quantitative robustness information for a variety of estimates. 1980
A completely revised and expanded edition of a classic resource
In the over twenty years since the publication of the Second Edition of Order Statistics, the theories and applications of this dynamic field have changed markedly. Meeting the challenges and demands of today’s students and research community, authors H. A. David and H. N. Nagaraja return with a completely revised and updated Order Statistics, Third Edition.
Chapters two through nine of this comprehensive volume deal with finite-sample theory, with individual topics grouped under distribution theory (chapters two through six) and statistical inference (chapters seven through nine). Chapters ten and eleven cover asymptotic theory for central, intermediate, and extreme order statistics, representing twice the coverage of this subject than the previous edition. New sections include:
- Stochastic orderings
- Characterizations
- Distribution-free prediction intervals
- Bootstrap estimations
- Moving order statistics
- Studentized range
- Ranked-set sampling
- Estimators of tail index
The authors further explain application procedures for many data-analysis techniques and quality control. An appendix provides a guide to related tables and computer algorithms. Extensive exercise sets have been updated since the last edition. In spite of many eliminations, the total number of references has increased from 1,000 to 1,500.
Expanded coverage of shortcut methods, robust estimation, life testing, reliability, L-statistics, and extreme-value theory complete this one-of-a-kind resource. Students and researchers of order statistics will appreciate this updated and thorough edition.
