Periodic version of the minimax distance criterion for Monte Carlo integration. (November 2020)
- Record Type:
- Journal Article
- Title:
- Periodic version of the minimax distance criterion for Monte Carlo integration. (November 2020)
- Main Title:
- Periodic version of the minimax distance criterion for Monte Carlo integration
- Authors:
- Eliáš, Jan
Vořechovský, Miroslav
Sadílek, Václav - Abstract:
- Highlights: numerical integration with designs optimized via miniMax (mM) criterion is developed. mM designs with standard metric are nonuniform which may cause biased integration. the proposed periodic metric ensures point uniformity and unbiased robust integration. efficient construction algorithm for mM designs (standard or periodic) is developed. Abstract: The selection of points for numerical integration of the Monte Carlo type, largely used in analysis of engineering problems, is developed. It is achieved by modification of the metric in the minimax optimality criterion. The standard minimax criterion ensures the design exhibits good space-filling property and therefore reduces the variance of the estimator of the integral. We, however, show that the points are not selected with the same probability over the space of sampling probabilities: some regions are over- or under-sampled when designs are generated repetitively. This violation of statistical uniformity may lead to systematically biased integral estimators. We propose that periodic metric be considered for calculation of the minimax distance. Such periodic minimax criterion provides statistically uniform designs leading to unbiased integration results and also low estimator variance due to retained space-filling property. These conclusions are demonstrated by examples integrating analytical functions. The designs are constructed by two different algorithms: (i) a new time-stepping algorithm resembling a dampedHighlights: numerical integration with designs optimized via miniMax (mM) criterion is developed. mM designs with standard metric are nonuniform which may cause biased integration. the proposed periodic metric ensures point uniformity and unbiased robust integration. efficient construction algorithm for mM designs (standard or periodic) is developed. Abstract: The selection of points for numerical integration of the Monte Carlo type, largely used in analysis of engineering problems, is developed. It is achieved by modification of the metric in the minimax optimality criterion. The standard minimax criterion ensures the design exhibits good space-filling property and therefore reduces the variance of the estimator of the integral. We, however, show that the points are not selected with the same probability over the space of sampling probabilities: some regions are over- or under-sampled when designs are generated repetitively. This violation of statistical uniformity may lead to systematically biased integral estimators. We propose that periodic metric be considered for calculation of the minimax distance. Such periodic minimax criterion provides statistically uniform designs leading to unbiased integration results and also low estimator variance due to retained space-filling property. These conclusions are demonstrated by examples integrating analytical functions. The designs are constructed by two different algorithms: (i) a new time-stepping algorithm resembling a damped system of attracted particles developed here, and (ii) the heuristic swapping of coordinates. The designs constructed by the time-stepping algorithm are attached to the paper as a supplementary material. The computer code for construction of the designs is attached too. … (more)
- Is Part Of:
- Advances in engineering software. Volume 149(2020)
- Journal:
- Advances in engineering software
- Issue:
- Volume 149(2020)
- Issue Display:
- Volume 149, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 149
- Issue:
- 2020
- Issue Sort Value:
- 2020-0149-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-11
- Subjects:
- Numerical integration -- Design of experiments -- Space-filling designs -- Latin hypercube sampling -- Voronoï tessellation -- Periodic space
Computer-aided engineering -- Periodicals
Engineering -- Computer programs -- Periodicals
Engineering -- Software -- Periodicals
Periodicals
620.0028553 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09659978 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.advengsoft.2020.102900 ↗
- Languages:
- English
- ISSNs:
- 0965-9978
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0705.450000
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British Library HMNTS - ELD Digital store - Ingest File:
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