English

Asymptotic Normality of Scrambled Geometric Net Quadrature

Statistics Theory 2016-04-28 v3 Numerical Analysis Computation Statistics Theory

Abstract

In a very recent work, Basu and Owen (2015) propose the use of scrambled geometric nets in numerical integration when the domain is a product of ss arbitrary spaces of dimension dd having a certain partitioning constraint. It was shown that for a class of smooth functions, the integral estimate has variance O(n12/d(logn)s1)O( n^{-1 -2/d} (\log n)^{s-1}) for scrambled geometric nets, compared to O(n1)O(n^{-1}) for ordinary Monte Carlo. The main idea of this paper is to develop on the work by Loh (2003), to show that the scrambled geometric net estimate has an asymptotic normal distribution for certain smooth functions defined on products of suitable subsets of Rd\mathbb{R}^d.

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Cite

@article{arxiv.1601.05842,
  title  = {Asymptotic Normality of Scrambled Geometric Net Quadrature},
  author = {Kinjal Basu and Rajarshi Mukherjee},
  journal= {arXiv preprint arXiv:1601.05842},
  year   = {2016}
}

Comments

41 pages, 6 figures