Chessboard distributions and random vectors with specified marginals and covariance matrix
成果类型：
Article
署名作者：
Ghosh, S; Henderson, SG
署名单位：
Cornell University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.50.5.820.364
发表日期：
2002
页码：
820-834
关键词：
摘要：
There is a growing need for the ability to specify and generate correlated random variables as primitive inputs to stochastic models Motivated by this need several authors have explored the generation of random vectors with specified marginals together with a specified covariance matrix through the use of a transformation of a multivariate normal random vector (the NORTA method) A covariance matrix is said to be feasible for a given set of marginal distributions if a random vector exists with these characteristics We develop a computational approach for establishing whether a given covariance matrix is feasible for a given set of marginals The approach is used to rigorously establish that there are sets of marginals with feasible covariance matrix that the NORTA method cannot match In such cases we show how to modify the initialization phase of NORTA so that it will exactly match the marginals and approximately match the desired covariance matrix An important feature of our analysis is that we show that for almost any covariance matrix (in a certain precise sense) our computational procedure either explicitly provides a construction of a random vector with the required properties or establishes that no such random vector exists.