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  • The objective of this paper is a study of performance of correlation control of recently proposed procedure for sampling from a multivariate population within the framework of Monte Carlo simulations (especially Latin Hypercube Sampling). In particular, we study the ability of the method to fulfill the prescribed correlation structure of a random vector for various sample sizes and number of marginal variables. Two norms of correlation error are defined, one very conservative and related to extreme errors and other related to averages of correlation errors. We study the behavior of Pearson correlation coefficient for Gaussian vectors and Spearman rank order coefficient (as a distribution-free correlation measure). Theoretical results on performance bounds for both correlation types in the case of desired uncorrelatedness are compared to performance of the proposed technique and also to other previously developed techniques for correlation control, namely the Cholesky orthogonalization as applied by Im
  • The objective of this paper is a study of performance of correlation control of recently proposed procedure for sampling from a multivariate population within the framework of Monte Carlo simulations (especially Latin Hypercube Sampling). In particular, we study the ability of the method to fulfill the prescribed correlation structure of a random vector for various sample sizes and number of marginal variables. Two norms of correlation error are defined, one very conservative and related to extreme errors and other related to averages of correlation errors. We study the behavior of Pearson correlation coefficient for Gaussian vectors and Spearman rank order coefficient (as a distribution-free correlation measure). Theoretical results on performance bounds for both correlation types in the case of desired uncorrelatedness are compared to performance of the proposed technique and also to other previously developed techniques for correlation control, namely the Cholesky orthogonalization as applied by Im (en)
Title
  • On correlation control in Monte Carlo type sampling
  • On correlation control in Monte Carlo type sampling (en)
skos:prefLabel
  • On correlation control in Monte Carlo type sampling
  • On correlation control in Monte Carlo type sampling (en)
skos:notation
  • RIV/00216305:26110/10:PU90719!RIV11-MSM-26110___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(KJB201720902), Z(MSM0021630519)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
http://linked.open...titaPredkladatele
http://linked.open...dnocenehoVysledku
  • 276683
http://linked.open...ai/riv/idVysledku
  • RIV/00216305:26110/10:PU90719
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • statistical correlation distribution, uncorrelatedness,, orthogonality, ortogonal vectors, multivariate Monte Carlo simulation, Latin Hypercube Sampling, correlation performance, saturated design (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [903C60C17FAE]
http://linked.open...v/mistoKonaniAkce
  • Singapur
http://linked.open...i/riv/mistoVydani
  • Singapur
http://linked.open...i/riv/nazevZdroje
  • Workshop on Reliable Engineering Computing (Robust Design - Coping with Hazards, Risk und Uncertainty)
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Vořechovský, Miroslav
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
http://linked.open...n/vavai/riv/zamer
number of pages
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  • Neuveden
https://schema.org/isbn
  • 978-981-08-5118-7
http://localhost/t...ganizacniJednotka
  • 26110
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