Name
Abstract | ||
|---|---|---|
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 Cramer-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 | DOI | Venue |
|---|---|---|
2009 | 10.1016/j.csda.2009.04.004 | Computational Statistics & Data Analysis |
Keywords | Field | DocType |
generalized cram,marginal distribution,multivariate distribution,monte carlo test procedure,multivariate cramer-von mises statistic,goodness-of-fit test,joint distribution,multivariate continuous distribution,multivariate kolmogorov-smirnov statistic,simulation shows,finite-sample p-values,goodness of fit test,kolmogorov smirnov,goodness of fit | Multivariate t-distribution,Econometrics,Multivariate stable distribution,Cramér–von Mises criterion,Multivariate statistics,Hotelling's T-squared distribution,Statistics,Inverse-Wishart distribution,Normal-Wishart distribution,Mathematics,Matrix t-distribution | Journal |
Volume | Issue | ISSN |
53 | 11 | Computational Statistics and Data Analysis |
Citations | PageRank | References |
7 | 0.74 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sung Nok Chiu | 1 | 12 | 3.37 |
| Kwong Ip Liu | 2 | 9 | 2.15 |