A heuristic approach for the generation of multivariate random samples with specified marginal distributions and correlation matrix

Charmpis, DC; Panteli, PL

dc.contributor.author	Charmpis, DC	en
dc.contributor.author	Panteli, PL	en
dc.date.accessioned	2014-03-01T01:19:45Z
dc.date.available	2014-03-01T01:19:45Z
dc.date.issued	2004	en
dc.identifier.issn	0943-4062	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15697
dc.subject	Correlation matrix	en
dc.subject	Multivariate distribution	en
dc.subject	Random number generation	en
dc.subject	Simulated annealing	en
dc.subject	Simulation	en
dc.subject.classification	Statistics & Probability	en
dc.subject.other	VARIABLES	en
dc.title	A heuristic approach for the generation of multivariate random samples with specified marginal distributions and correlation matrix	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/BF02892061	en
heal.identifier.secondary	http://dx.doi.org/10.1007/BF02892061	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	This paper presents a heuristic approach for multivariate random number generation. Our aim is to generate multivariate samples with specified marginal distributions and correlation matrix, which can be incorporated into risk analysis models to conduct simulation studies. The proposed sampling approach involves two distinct steps: first a univariate random sample from each specified probability distribution is generated; then a heuristic combinatorial optimization procedure is used to rearrange the generated univariate samples, in order to obtain the desired correlations between them. The combinatorial optimization step is performed with a simulated annealing algorithm, which changes only the positions and not the values of the numbers generated in the first step. The proposed multivariate sampling approach can be used with any type of marginal distributions: continuous or discrete, parametric or non-parametric, etc.	en
heal.publisher	PHYSICA-VERLAG GMBH & CO	en
heal.journalName	Computational Statistics	en
dc.identifier.doi	10.1007/BF02892061	en
dc.identifier.isi	ISI:000221973500008	en
dc.identifier.volume	19	en
dc.identifier.issue	2	en
dc.identifier.spage	283	en
dc.identifier.epage	300	en