Hierarchical refinement of Latin Hypercube Samples

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F14%3APU112316" target="_blank" >RIV/00216305:26110/14:PU112316 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216305:26110/15:PU115750

Výsledek na webu

<a href="http://dx.doi.org/10.1111/mice.12088" target="_blank" >http://dx.doi.org/10.1111/mice.12088</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/mice.12088" target="_blank" >10.1111/mice.12088</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Hierarchical refinement of Latin Hypercube Samples

Popis výsledku v původním jazyce

The objective In this article, a novel method for the extension of sample size in Latin Hypercube Sampling (LHS) is suggested. The method can be applied when an initial LH design is employed for the analysis of functions g of a random vector. The article explains how the statistical, sensitivity and reliability analyses of g can be divided into a hierarchical sequence of simulations with subsets of samples of a random vector in such a way that (i) the favorable properties of LHS are retained (the low number of simulations needed for statistically significant estimations of statistical parameters of function g with low estimation variability); (ii) the simulation process can be halted, for example, when the estimations reach a certain prescribed statistical significance. An important aspect of the method is that it efficiently simulates subsets of samples of random vectors while focusing on their correlation structure or any other objective function such as some measure of dependence, spatial distribution uniformity, discrepancy, etc. This is achieved by employing a robust algorithm based on combinatorial optimization of the mutual ordering of samples. The method is primarily intended to serve as a tool for computationally intensive evaluations of g where there is a need for pilot numerical studies, preliminary and subsequently refined estimations of statistical parameters, optimization of the progressive learning of neural networks, or during experimental design.

Název v anglickém jazyce

Hierarchical refinement of Latin Hypercube Samples

Popis výsledku anglicky

The objective In this article, a novel method for the extension of sample size in Latin Hypercube Sampling (LHS) is suggested. The method can be applied when an initial LH design is employed for the analysis of functions g of a random vector. The article explains how the statistical, sensitivity and reliability analyses of g can be divided into a hierarchical sequence of simulations with subsets of samples of a random vector in such a way that (i) the favorable properties of LHS are retained (the low number of simulations needed for statistically significant estimations of statistical parameters of function g with low estimation variability); (ii) the simulation process can be halted, for example, when the estimations reach a certain prescribed statistical significance. An important aspect of the method is that it efficiently simulates subsets of samples of random vectors while focusing on their correlation structure or any other objective function such as some measure of dependence, spatial distribution uniformity, discrepancy, etc. This is achieved by employing a robust algorithm based on combinatorial optimization of the mutual ordering of samples. The method is primarily intended to serve as a tool for computationally intensive evaluations of g where there is a need for pilot numerical studies, preliminary and subsequently refined estimations of statistical parameters, optimization of the progressive learning of neural networks, or during experimental design.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

20101 - Civil engineering

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computer-Aided Civil and Infrastructure Engineering

ISSN

1093-9687

e-ISSN

1467-8667

Svazek periodika

2014

Číslo periodika v rámci svazku

00

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

18

Strana od-do

1-18

Kód UT WoS článku

000352790800006

EID výsledku v databázi Scopus

2-s2.0-84926526361