Detail publikace

Performance of Various Sampling Schemes in Asymptotic Sampling

ŠMÍDOVÁ, M. VOŘECHOVSKÝ, M.

Originální název

Performance of Various Sampling Schemes in Asymptotic Sampling

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This article deals with the possibility to use Asymptotic Sampling (AS) for estimation of failure probability. The AS algorithm requires samples of multidimensional Gaussian random vector. There are many alternatives how to obtain such a sample and the selection of sampling strategy influences the performance of the AS method. Several reliability problems (testing functions) are selected to test AS with various sampling schemes. First, the functions are analyzed using AS in combination with (i) Monte Carlo designs, (ii) LHS designs optimized using Periodic Audze-Eglājs (PAE) criterion and, (iii) designs prepared using Sobol sequences. Afterwards, the same set of problems has been solved without the AS procedure by direct estimation of failure probability. All the results are also compared with the exact value of the failure probability.

Klíčová slova

Failure probability; Asymptotic Sampling; Monte Carlo (MC); Latin Hypercube Sampling (LHS); Quasi Monte Carlo (QMC)

Autoři

ŠMÍDOVÁ, M.; VOŘECHOVSKÝ, M.

Vydáno

5. 12. 2016

Nakladatel

Springer International Publishing AG 2017

Místo

Ghent

ISBN

978-3-319-47885-2

Kniha

14th International Probabilistic Workshop

Strany od

45

Strany do

61

Strany počet

17

BibTex

@inproceedings{BUT133092,
  author="Magdalena {Martinásková} and Miroslav {Vořechovský}",
  title="Performance of Various Sampling Schemes in Asymptotic Sampling",
  booktitle="14th International Probabilistic Workshop",
  year="2016",
  pages="45--61",
  publisher="Springer International Publishing AG 2017",
  address="Ghent",
  doi="10.1007/978-3-319-47886-9",
  isbn="978-3-319-47885-2"
}