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On Multivariate Vertical Density Representation and its Application to Random Number Generation
Authors:
Samuel Kotz a;
Kai-Tai Fang b;
Jia-Juan Liang b
| Affiliations: | a University of Maryland, College Park, USA |
| b Hong Kong Baptist University and Academia Sinica, Beijing, China |
DOI:
10.1080/02331889708802607
Publication Frequency:
6 issues per year
Subjects:
Mathematical Statistics;
Statistical Theory & Methods;
Statistics;
Statistics for the Biological Sciences;
Stochastic Models & Processes;
Formats available:
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(English)
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Abstract
Motivated by the works of Troutt (1991, 1993) and Kotz and Troutt (1996), we provide a multivariate definition of the vertical density representation (vdr) and calculate its value for some basic multivariate distributions presented in Fang et al. (1990) and Johnson (1987). Utilizing the multivariate vdr and the theorem of Troutt (1993) we generalize the well-known Box-Muller method to generate the basic multivariate distributions.
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| Keywords: Vertical density representation; Box-Muller method; spherically symmetric distribution; L1-norm symmetric distribution; Lp-norm symmetric distribution |
| 1991 Mathematical Subject Classfication: 6209; 62H10; 62H15 |
| view references (8) |
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