A heuristic approach for the generation of multivariate random samples with specified marginal distributions and correlation matrix |
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Authors: | Dimos C Charmpis Panayiota L Panteli |
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Institution: | (1) Institute of Structural Analysis and Seismic Research, National Technical University of Athens, 9, Iroon Polytechniou Str., Zografou Campus, GR-15780 Athens, Greece;(2) Economics Research Center, University of Cyprus, P.O. Box 20537, CY-1678 Nicosia, Cyprus |
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Abstract: | Summary 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. |
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Keywords: | Simulation random number generation multivariate distribution correlation matrix simulated annealing |
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