ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1601.05842
42
10
v1v2v3 (latest)

Asymptotic Normality of Scrambled Geometric Net Quadrature

21 January 2016
Kinjal Basu
Rajarshi Mukherjee
ArXiv (abs)PDFHTML
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 sss arbitrary spaces of dimension ddd having a certain partitioning constraint. It was shown that for a class of smooth functions, the integral estimate has variance O(n−1−2/d(log⁡n)s−1)O( n^{-1 -2/d} (\log n)^{s-1})O(n−1−2/d(logn)s−1) for scrambled geometric nets, compared to O(n−1)O(n^{-1})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}^dRd.

View on arXiv
Comments on this paper