Sliced Latin hypercube designs with arbitrary run sizes

2019/05/07 by Jin Xu, Xu, Jin, Xu He +5
Computer Science · Decision Sciences · Engineering · #Advanced Multi-Objective Optimization Algorithms #Applications (stat.AP) #FOS: Computer and information sciences #FOS: Mathematics #Optimal Experimental Design Methods #Optimization and Packing Problems #Statistics Theory (math.ST)

paper · pdf · doi:10.48550/arxiv.1905.02721

openalex publication_date 2019/05/07 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Latin hypercube designs achieve optimal univariate stratifications and are useful for computer experiments. Sliced Latin hypercube designs are Latin hypercube designs that can be partitioned into smaller Latin hypercube designs. In this work, we give, to the best of our knowledge, the first construction of sliced Latin hypercube designs that allow arbitrarily chosen run sizes for the slices. We also provide an algorithm to reduce correlations of our proposed designs.

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