Error estimation in high dimensional space for stochastic collocation methods on arbitrary sparse samples

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We have develop a fast method that can give high order error estimates of piecewise smooth functions in high dimensions with high order and low computational cost. This method can be used polynomial annihilation to estimate the smoothness of local regions of arbitrary samples in annihilation stochastic simulations. We compare the error estimation of this method to gaussian process error estimation techniques.

Original languageEnglish
Title of host publication11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013
Pages906-909
Number of pages4
DOIs
StatePublished - 2013
Event11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013 - Rhodes, Greece
Duration: Sep 21 2013Sep 27 2013

Publication series

NameAIP Conference Proceedings
Volume1558
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference11th International Conference of Numerical Analysis and Applied Mathematics 2013, ICNAAM 2013
Country/TerritoryGreece
CityRhodes
Period09/21/1309/27/13

Keywords

  • Uncertainty quantification
  • sampling

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