Publication detail

Performance of Various Sampling Schemes in Asymptotic Sampling

ŠMÍDOVÁ, M. VOŘECHOVSKÝ, M.

Original Title

Performance of Various Sampling Schemes in Asymptotic Sampling

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

ŠMÍDOVÁ, M.; VOŘECHOVSKÝ, M.

Released

5. 12. 2016

Publisher

Springer International Publishing AG 2017

Location

Ghent

ISBN

978-3-319-47885-2

Book

14th International Probabilistic Workshop

Pages from

45

Pages to

61

Pages count

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"
}