On the Use of Columnwise-Pairwise Algorithm for Generating Correlated Multivariate Random Samples
Simulation technique has gained a wide attention in many fields as a crucial method to study the relationship between the input variables and output response in complex systems. The generation of random samples from multivariate distribution is a common requirement in the context of simulation. This paper presents an application of Columnwise-pairwise algorithm (CP) for generating correlated multivariate random samples when the marginal distribution and correlation matrix are pre-specified. The proposed method is compared with the existing method namely Simulated annealing algorithm (SA). The results show that CP performs well and is comparable to SA while CP requires less parameter and the structure is less complex than SA. Hence the proposed method is recommended for use in any Monte Carlo methods such as risk analysis models and computer simulated experiments, etc.
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