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

14 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
General Mathematics
Agricultural and Biological Sciences (miscellaneous)
General Agricultural and Biological Sciences
Statistics, Probability and Uncertainty
Applied Mathematics

Keywords

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

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10.1093/biomet/asq051

Cite this

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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}",

note = "Funding Information: The authors are grateful to a reviewer for pointing out an error leading to a substantial improvement of the paper and to another reviewer for helpful editorial comments. Their research is supported by grants from the National Science Foundation, U.S.A.",

year = "2010",

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doi = "10.1093/biomet/asq051",

language = "English (US)",

volume = "97",

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T2 - Probability-based Latin hypercube designs for slid-rectangular regions

AU - Hung, Ying

AU - Amemiya, Yasuo

AU - Wu, Chien Fu Jeff

N1 - Funding Information: The authors are grateful to a reviewer for pointing out an error leading to a substantial improvement of the paper and to another reviewer for helpful editorial comments. Their research is supported by grants from the National Science Foundation, U.S.A.

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Y1 - 2010/12

N2 - 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.

AB - 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.

KW - Computer experiment

KW - Heuristic search

KW - Latin hypercube design

KW - Sampling

KW - Space-filling design

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

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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