Multivariate distributions and the moment problem
| Autor: | Jordan Stoyanov, Christian Kleiber |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Statistics and Probability
Stieltjes class Numerical Analysis Multivariate statistics Kotz-type distribution Univariate Multivariate normal distribution Multi-indexed moments Normal-Wishart distribution Copula (probability theory) Moment problem Univariate distribution Copula Elliptically contoured distribution Multidimensional moment problem Multivariate distributions Calculus Applied mathematics Weibull distribution Multivariate t-distribution Statistics Probability and Uncertainty Mathematics |
| Zdroj: | Journal of Multivariate Analysis. 113:7-18 |
| ISSN: | 0047-259X |
| DOI: | 10.1016/j.jmva.2011.06.001 |
| Popis: | For any multivariate distribution with finite moments we can ask, as in the univariate case, whether or not the distribution is uniquely determined by its moments. In this paper, we summarize, unify and extend some results that are widely scattered in the mathematical and statistical literature. We present some new results showing how to use univariate criteria together with other arguments to characterize the moment (in)determinacy of multivariate distributions. Among our examples are some classical multivariate distributions including the class of elliptically contoured distributions. Kotz-type distributions receive particular attention. We also describe some Stieltjes classes comprising distinct multivariate distributions that all possess the same set of moments. Some challenging open questions in this area are briefly outlined. |
| Databáze: | OpenAIRE |
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