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Making a substantiated choice of the most efficient statistical test is one of the basic problems of statistics. Asymptotic efficiency is an indispensable technique for comparing and ordering statistical tests in large samples. It is especially useful in nonparametric statistics where it is usually necessary to rely on heuristic tests. This monograph presents a unified treatment of the analysis and calculation of the asymptotic efficiencies of nonparametric tests. Powerful new methods are developed to evaluate explicitly different kinds of efficiencies. Of particular interest is the description of domains of the Bahadur local optimality and related characterization problems based on recent research by the author. Other Russian results are also published here for the first time in English. Researchers, professionals, and students in statistics will find this book invaluable.Read more
- First unified treatment of the subject, brings together results scattered through the literature
- Develops powerful new methods
- Contains Russian results not well known in the West
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"...gives a unifying view of the state of the art in this area." Noel Veraverbeke, Mathematical Reviews
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- Date Published: July 2009
- format: Paperback
- isbn: 9780521115926
- length: 296 pages
- dimensions: 229 x 152 x 17 mm
- weight: 0.44kg
- availability: Available
Table of Contents
1. Asymptotic efficiency of statistical tests and mathematical means for its computation
2. Asymptotic efficiency of nonparametric goodness-of-fit tests
3. Asymptotic efficiency of nonparametric homogeneity tests
4. Asymptotic efficiency of nonparametric symmetry tests
5. Asymptotic efficiency of nonparametric independence tests
6. Local asymptotic optimality of nonparametric tests and the characterisation of distributions.
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