Miscellanea: Probability-based Latin hypercube designs for slid-rectangular regions

Ying Hung; Yasuo Amemiya; Chien Fu Jeff Wu

doi:10.1093/biomet/asq051

Miscellanea: Probability-based Latin hypercube designs for slid-rectangular regions

Ying Hung, Yasuo Amemiya, Chien Fu Jeff Wu

School of Arts and Sciences, Statistics

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

Existing space-filling designs are based on the assumption that the experimental region is rectangular, while in practice this assumption can be violated. Motivated by a data centre thermal management study, a class of probability-based Latin hypercube designs is proposed to accommodate a specific type of irregular region. A heuristic algorithm is proposed to search efficiently for optimal designs. Unbiased estimators are proposed, their variances are given and their performances are compared empirically. The proposed method is applied to obtain an optimal sensor placement plan to monitor and study the thermal distribution in a data centre.

Original language	English (US)
Pages (from-to)	961-968
Number of pages	8
Journal	Biometrika
Volume	97
Issue number	4
DOIs	https://doi.org/10.1093/biomet/asq051
State	Published - Dec 2010

All Science Journal Classification (ASJC) codes

Statistics and Probability
Mathematics(all)
Agricultural and Biological Sciences (miscellaneous)
Agricultural and Biological Sciences(all)
Statistics, Probability and Uncertainty
Applied Mathematics

Keywords

Computer experiment
Heuristic search
Latin hypercube design
Sampling
Space-filling design

Access to Document

10.1093/biomet/asq051

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abstract = "Existing space-filling designs are based on the assumption that the experimental region is rectangular, while in practice this assumption can be violated. Motivated by a data centre thermal management study, a class of probability-based Latin hypercube designs is proposed to accommodate a specific type of irregular region. A heuristic algorithm is proposed to search efficiently for optimal designs. Unbiased estimators are proposed, their variances are given and their performances are compared empirically. The proposed method is applied to obtain an optimal sensor placement plan to monitor and study the thermal distribution in a data centre.",

keywords = "Computer experiment, Heuristic search, Latin hypercube design, Sampling, Space-filling design",

author = "Ying Hung and Yasuo Amemiya and Wu, {Chien Fu Jeff}",

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