Generalized Cramér-von Mises goodness-of-fit tests for multivariate distributions
A class of statistics for testing the goodness-of-fit for any multivariate continuous distribution is proposed. These statistics consider not only the goodness-of-fit of the joint distribution but also the goodness-of-fit of all marginal distributions, and can be regarded as generalizations of the multivariate Cramér-von Mises statistic. Simulation shows that these generalizations, using the Monte Carlo test procedure to approximate their finite-sample p-values, are more powerful than the multivariate Kolmogorov-Smirnov statistic.
Year of publication: |
2009
|
---|---|
Authors: | Chiu, Sung Nok ; Liu, Kwong Ip |
Published in: |
Computational Statistics & Data Analysis. - Elsevier, ISSN 0167-9473. - Vol. 53.2009, 11, p. 3817-3834
|
Publisher: |
Elsevier |
Saved in:
Saved in favorites
Similar items by person
-
Chiu, Sung Nok, (2010)
-
Stationarity Tests for Spatial Point Processes using Discrepancies
Chiu, Sung Nok, (2013)
-
Homogeneity tests for several Poisson populations
Chiu, Sung Nok, (2009)
- More ...