Journal
ASTA-ADVANCES IN STATISTICAL ANALYSIS
Volume 94, Issue 4, Pages 341-351Publisher
SPRINGER
DOI: 10.1007/s10182-010-0145-y
Keywords
Computer experiments; Space-filling designs; Optimal Latin hypercube designs; Kullback-Leibler information
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Space-filling designs are commonly used for selecting the input values of time-consuming computer codes. Computer experiment context implies two constraints on the design. First, the design points should be evenly spread throughout the experimental region. A space-filling criterion (for instance, the maximin distance) is used to build optimal designs. Second, the design should avoid replication when projecting the points onto a subset of input variables (non-collapsing). The Latin hypercube structure is often enforced to ensure good projective properties. In this paper, a space-filling criterion based on the Kullback-Leibler information is used to build a new class of Latin hypercube designs. The new designs are compared with several traditional optimal Latin hypercube designs and appear to perform well.
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