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Probability-based Latin hypercube designs for slid-rectangular regions

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  • Ying Hung
  • Yasuo Amemiya
  • Chien-Fu Jeff Wu

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. Copyright 2010, Oxford University Press.

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  • Ying Hung & Yasuo Amemiya & Chien-Fu Jeff Wu, 2010. "Probability-based Latin hypercube designs for slid-rectangular regions," Biometrika, Biometrika Trust, vol. 97(4), pages 961-968.
    • Handle: RePEc:oup:biomet:v:97:y:2010:i:4:p:961-968
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    File URL: http://hdl.handle.net/10.1093/biomet/asq051
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    Cited by:

    1. Chen, Ray-Bing & Hsu, Yen-Wen & Hung, Ying & Wang, Weichung, 2014. "Discrete particle swarm optimization for constructing uniform design on irregular regions," Computational Statistics & Data Analysis, Elsevier, vol. 72(C), pages 282-297.

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