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The subject of this book is to present a new approach of obtaining resampling approximations to the sampling null distributions of tests in various cases. The cases include the testing for multivariate distributions, location problems, the adequacy of parametric as well as semiparametric models, heteroscedasticity of regression models and homogeneity of covariance matrices and some models with censored data.

Produktbeschreibung
The subject of this book is to present a new approach of obtaining resampling approximations to the sampling null distributions of tests in various cases. The cases include the testing for multivariate distributions, location problems, the adequacy of parametric as well as semiparametric models, heteroscedasticity of regression models and homogeneity of covariance matrices and some models with censored data.


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Autorenporträt
Lixing Zhu is Associate Professor of Statistics at the University of Hong Kong. He is a winner of the Humboldt Research Award at Alexander-von Humboldt Foundation of Germany and an elected Fellow of the Institute of Mathematical Statistics.
Rezensionen
From the reviews:

"These lecture notes discuss several topics in goodness-of-fit testing, a classical area in statistical analysis. ... The mathematical part contains detailed proofs of the theoretical results. Simulation studies illustrate the quality of the Monte Carlo approximation. ... this book constitutes a recommendable contribution to an active area of current research." Winfried Stute for Mathematical Reviews, Issue 2006

"...Overall, this is an interesting book, which gives a nice introduction to this new and specific field of resampling methods." Dongsheng Tu for Biometrics, September 2006

"Nonparametric Monte Carlo tests (NMCT) are more and more used everywhere when standard theory fails ... . The author of this concise monograph shows several fields where NMCT procedures can be effectively used ... . I recommend this book not only to everybody who is deeply interested in Monte Carlo simulations but also to those interested in asymptotics and bootstrap." (Jaromir Antoch, Zentralblatt MATH, Vol. 1094 (20), 2006)