A Universal Algorithm for Multivariate Integration

David Krieg; Erich Novak

A Universal Algorithm for Multivariate Integration

Numerical Analysis 2016-02-02 v2

Authors: David Krieg , Erich Novak

Abstract

We present an algorithm for multivariate integration over cubes that is unbiased and has optimal order of convergence (in the randomized sense as well as in the worst case setting) for all Sobolev spaces $H^{r, mix}([0,1]^d)$ and $H^s([0,1]^d)$ for $s>d/2$ .

Keywords

matrix algorithms

Cite

@article{arxiv.1507.06853,
  title  = {A Universal Algorithm for Multivariate Integration},
  author = {David Krieg and Erich Novak},
  journal= {arXiv preprint arXiv:1507.06853},
  year   = {2016}
}

Comments

To appear in Found. of Comput. Math

Related papers

View all related →