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Statements

Subject Item
n2:RIV%2F00216305%3A26110%2F11%3APU96410%21RIV13-AV0-26110___
rdf:type
skos:Concept n15:Vysledek
dcterms:description
The objective of this paper is twofold. Firstly to deliver theoretical bounds for performance of simulation techniques of Monte Carlo type measuring the ability to fulfill prescribed correlation matrices. Secondly, we study the performance in 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, other related to averages of correlation errors. We study 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 The objective of this paper is twofold. Firstly to deliver theoretical bounds for performance of simulation techniques of Monte Carlo type measuring the ability to fulfill prescribed correlation matrices. Secondly, we study the performance in 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, other related to averages of correlation errors. We study 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
dcterms:title
Correlation in probabilistic simulation Correlation in probabilistic simulation
skos:prefLabel
Correlation in probabilistic simulation Correlation in probabilistic simulation
skos:notation
RIV/00216305:26110/11:PU96410!RIV13-AV0-26110___
n15:predkladatel
n16:orjk%3A26110
n5:aktivita
n7:P
n5:aktivity
P(GAP105/11/1385), P(KJB201720902)
n5:dodaniDat
n6:2013
n5:domaciTvurceVysledku
n17:1352687
n5:druhVysledku
n21:D
n5:duvernostUdaju
n13:S
n5:entitaPredkladatele
n14:predkladatel
n5:idSjednocenehoVysledku
192051
n5:idVysledku
RIV/00216305:26110/11:PU96410
n5:jazykVysledku
n20:eng
n5:klicovaSlova
Correlation in probabilistic simulation
n5:klicoveSlovo
n18:Correlation%20in%20probabilistic%20simulation
n5:kontrolniKodProRIV
[C4807F4353A0]
n5:mistoKonaniAkce
Zurich
n5:mistoVydani
Zurich, Švýcarsko
n5:nazevZdroje
Applications of Statistics and Probability in Civil Engineering
n5:obor
n11:JM
n5:pocetDomacichTvurcuVysledku
1
n5:pocetTvurcuVysledku
1
n5:projekt
n8:KJB201720902 n8:GAP105%2F11%2F1385
n5:rokUplatneniVysledku
n6:2011
n5:tvurceVysledku
Vořechovský, Miroslav
n5:typAkce
n12:EUR
n5:zahajeniAkce
2011-08-01+02:00
s:numberOfPages
8
n19:hasPublisher
Neuveden
n22:isbn
978-0-415-66986-3
n3:organizacniJednotka
26110