Statistical tests of nonparametric hypotheses : asymptotic theory / Odile Pons.
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TextPublication details: Singapore : World Scientific, ©2014.Description: x, 293 pages : illustrations ; 24 cmISBN: - 9789814531740 (hard cover : alk. paper)
- 000SA.12 23 P798
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.12 P798 (Browse shelf(Opens below)) | Available | 137815 |
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| 000SA.12 L523 Nonparametrics | 000SA.12 L754 Nonparametric statistics for applied research / | 000SA.12 P314 Nonparametric statistics on manifolds and their applications to object data analysis / | 000SA.12 P798 Statistical tests of nonparametric hypotheses : | 000SA.12 Si571 Nonparametric statistics for the behavioural sciences | 000SA.12=4 R215 Statistique non parametric asymptotique | 000SA.13 D229 Robust response surfaces, regression, and positive data analyses / |
Includes bibliographical references and index.
1. Introduction --
2. Asymptotic Theory --
3. Nonparametric tests for one sample --
4. Two-sample tests --
5. Multi-dimensional tests --
6. Nonparametric tests for processes --
7. Nonparametric tests under censoring or truncation --
8. Sequential tests --
Appendix.
An overview of the asymptotic theory of optimal nonparametric tests is presented in this book. It covers a wide range of topics: Neyman-Pearson and LeCam's theories of optimal tests, the theories of empirical processes and kernel estimators with extensions of their applications to the asymptotic behavior of tests for distribution functions, densities and curves of the nonparametric models defining the distributions of point processes and diffusions. With many new test statistics developed for smooth curves, the reliance on kernel estimators with bias corrections and the weak convergence of the estimators are useful to prove the asymptotic properties of the tests, extending the coverage to semiparametric models. They include tests built from continuously observed processes and observations with cumulative intervals.
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