Adaptive Probability-Based Latin Hypercube Designs

Abstract

Adaptive sampling is an effective method developed mainly for regular regions. However, experimental regions in irregular shapes are commonly observed in practice. Motivated by a data center thermal management study, a new class of adaptive designs is proposed to accommodate a specific type of irregular region. Because the adaptive procedure introduces biases into conventional estimators, several design-unbiased estimators are given for estimating the population mean. Efficient and easy-to-compute unbiased estimators are also introduced. The proposed method is applied to obtain an adaptive sensor placement plan to monitor and study the thermal distribution in a data center. All of the supplemental materials used in this work are available online.

Keywords:  :

• Adaptive cluster sampling
• Computer experiment
• Latin hypercube design
• Rao–Blackwell method
• Sequential design
• Space-filling design