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Statements

Subject Item
n2:RIV%2F00216305%3A26110%2F12%3APU102793%21RIV13-GA0-26110___
rdf:type
skos:Concept n9:Vysledek
dcterms:description
In this paper, we suggest principles of a novel simulation method for analyses of functions g(X) of a random vector X, suitable for the cases when the evaluation of g(X) is very expensive. The method is based on Latin Hypercube Sampling strategy. The paper explains how the statistical, sensitivity and reliability analysis of g(X) can be divided into a hierarchical sequence of simulations with subsets of samples of a random vector X such that (i) the favorable properties of LHS are retained (low number of simulations needed for significant estimations of statistics of g(X) with a low variability of the estimation); (ii) all subsets can anytime be merged into one set while keeping its consistency (the simulation process can be halted e.g., when reaching a certain prescribed statistical significance of the estimations). An important aspect of the method is that it efficiently simulates subsets of samples of random vectors with focus on their correlation structure. In this paper, we suggest principles of a novel simulation method for analyses of functions g(X) of a random vector X, suitable for the cases when the evaluation of g(X) is very expensive. The method is based on Latin Hypercube Sampling strategy. The paper explains how the statistical, sensitivity and reliability analysis of g(X) can be divided into a hierarchical sequence of simulations with subsets of samples of a random vector X such that (i) the favorable properties of LHS are retained (low number of simulations needed for significant estimations of statistics of g(X) with a low variability of the estimation); (ii) all subsets can anytime be merged into one set while keeping its consistency (the simulation process can be halted e.g., when reaching a certain prescribed statistical significance of the estimations). An important aspect of the method is that it efficiently simulates subsets of samples of random vectors with focus on their correlation structure.
dcterms:title
Extension of sample size in Latin Hypercube Sampling – methodology and software Extension of sample size in Latin Hypercube Sampling – methodology and software
skos:prefLabel
Extension of sample size in Latin Hypercube Sampling – methodology and software Extension of sample size in Latin Hypercube Sampling – methodology and software
skos:notation
RIV/00216305:26110/12:PU102793!RIV13-GA0-26110___
n9:predkladatel
n14:orjk%3A26110
n5:aktivita
n18:P
n5:aktivity
P(GAP105/11/1385), P(TA01011019)
n5:dodaniDat
n8:2013
n5:domaciTvurceVysledku
n21:1352687
n5:druhVysledku
n13:D
n5:duvernostUdaju
n22:S
n5:entitaPredkladatele
n15:predkladatel
n5:idSjednocenehoVysledku
135911
n5:idVysledku
RIV/00216305:26110/12:PU102793
n5:jazykVysledku
n10:eng
n5:klicovaSlova
Latin Hypercube Sampling, statistical, Monte Carlo
n5:klicoveSlovo
n11:Monte%20Carlo n11:Latin%20Hypercube%20Sampling n11:statistical
n5:kontrolniKodProRIV
[A74F7CEDDB41]
n5:mistoKonaniAkce
Vienna
n5:mistoVydani
Austria, Vienna
n5:nazevZdroje
3rd Symposium on Life-Cycle and Sustainability of Civil Infrastructure Systems
n5:obor
n20:JM
n5:pocetDomacichTvurcuVysledku
1
n5:pocetTvurcuVysledku
1
n5:projekt
n16:TA01011019 n16:GAP105%2F11%2F1385
n5:rokUplatneniVysledku
n8:2012
n5:tvurceVysledku
Vořechovský, Miroslav
n5:typAkce
n12:WRD
n5:zahajeniAkce
2012-10-03+02:00
s:numberOfPages
8
n19:hasPublisher
Neuveden
n6:isbn
978-0-415-62126-7
n17:organizacniJednotka
26110