Nonparametric Monte Carlo Tests and Their Applications

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.

Especially for people working in the re-sampling approximation area or applying re-sampling approximations to other areas Re-sampling approximation has been one of the most important tools in statistical analysis and this book features a new approach as to apply it

Autorentext
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.

Inhalt
Monte Carlo Tests.- Testing for Multivariate Distributions.- Asymptotics of Goodness-of-fit Tests for Symmetry.- A Test of Dimension-Reduction Type for Regressions.- Checking the Adequacy of a Partially Linear Model.- Model Checking for Multivariate Regression Models.- Heteroscedasticity Tests for Regressions.- Checking the Adequacy of a Varying-Coefficients Model.- On the Mean Residual Life Regression Model.- Homegeneity Testing for Covariance Matrices.