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Nonparametric Monte Carlo Tests and Their Applications (Lecture Notes in Statistics (182)) by Lixing Zhu, Ph. D is a nonfiction available to read on EtoBox.

What is Nonparametric Monte Carlo Tests and Their Applications (Lecture Notes in Statistics (182)) about?

<p>A fundamental issue in statistical analysis is testing the fit of a particular probability model to a set of observed data. Monte Carlo approximation to the null distribution of the test provides a convenient and powerful means of testing model fit. Nonparametric Monte Carlo Tests and Their Applications proposes a new Monte Carlo-based methodology to construct this type of approximation when the model is semistructured. When there are no nuisance parameters to be estimated, the nonparametric Monte Carlo test can exactly maintain the significance level, and when nuisance parameters exist, this method can allow the test to asymptotically maintain the level.</p> <p>The author addresses both applied and theoretical aspects of nonparametric Monte Carlo tests. The new methodology has been used for model checking in many fields of statistics, such as multivariate distribution theory, parametric and semiparametric regression models, multivariate regression models, varying-coefficient models with longitudinal data, heteroscedasticity, and homogeneity of covariance matrices. This book will be of interest to both practitioners and researchers investigating goodness-of-fit tests and resampl

Who reads Nonparametric Monte Carlo Tests and Their Applications (Lecture Notes in Statistics (182))?

Author

Lixing Zhu, Ph. D

Publisher

Springer Science+Business Media, Inc

Published

2005

Language

EN

ISBN

9786610608232

Category

nonfiction

Subjects

Mathematics, Stem