Constructing Multivariate Distributions with Specific Marginal Distributions

K. J. Koehler and J. T. Symanowski

Journal of Multivariate Analysis, 1995, vol. 55, issue 2, 261-282

Abstract: A method is presented for constructing multivariate distributions with any specific set of univariate marginal distributions. This construction provides a rich class of distributions for modeling multivariate data as well as a basis for easily simulating correlated observations. The joint cdf and joint density function are expressed as explicit functions of the cdf's and density functions for the univariate marginal distributions. The inclusion of different association parameters for different subsets of variables allows for many different patterns of associations. General properties of this class of multivariate distributions are reviewed and contour plots of selected bivariate densities are presented to illustrate the variety of possible shapes. An application to multivariate survival analysis is briefly considered.

Date: 1995
References: Add references at CitEc
Citations: View citations in EconPapers (14)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047-259X(85)71079-2
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:55:y:1995:i:2:p:261-282

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().