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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…

Statistics Theory · Mathematics 2019-05-09 Jin Xu , Xu He , Xiaojun Duan , Zhengming Wang

New types of designs called nested space-filling designs have been proposed for conducting multiple computer experiments with different levels of accuracy. In this article, we develop several approaches to constructing such designs. The…

Statistics Theory · Mathematics 2009-09-04 Peter Z. G. Qian , Mingyao Ai , C. F. Jeff Wu

Latin hypercube sampling (LHS) is generalized in terms of a spectrum of stratified sampling (SS) designs referred to as partially stratified sample (PSS) designs. True SS and LHS are shown to represent the extremes of the PSS spectrum. The…

Computation · Statistics 2015-12-14 Michael D. Shields , Jiaxin Zhang

In this paper we use counting arguments to prove that the expected percentage coverage of a $d$ dimensional parameter space of size $n$ when performing $k$ trials with either Latin Hypercube sampling or Orthogonal sampling (when $n=p^d$) is…

Optimizing the reliability and the robustness of a design is important but often unaffordable due to high sample requirements. Surrogate models based on statistical and machine learning methods are used to increase the sample efficiency.…

Machine Learning · Statistics 2022-05-06 Can Bogoclu , Dirk Roos , Tamara Nestorović

This paper investigates the construction of space-filling designs for computer experiments. The space-filling property is characterized by the covering and separation radii of a design, which are integrated through the unified criterion of…

Methodology · Statistics 2026-02-18 Naoki Sakai , Takashi Goda

To identify the robust settings of the control factors, it is very important to understand how they interact with the noise factors. In this article, we propose space-filling designs for computer experiments that are more capable of…

Methodology · Statistics 2018-11-26 V. Roshan Joseph , Li Gu , Shan Ba , William R. Myers

Difference arrays are used in applications such as software testing, authentication codes and data compression. Pseudo-orthogonal Latin squares are used in experimental designs. A special class of pseudo-orthogonal Latin squares are the…

Combinatorics · Mathematics 2017-01-23 Fatih Demirkale , Diane M. Donovan , Joanne Hall , Abdollah Khodkar , Asha Rao

Semi-Latin squares have been extensively studied. They can be interpreted as a special case of latinized block designs where the number of columns is equal to the number of replicates in the design. Latinized row-column designs are…

Methodology · Statistics 2025-05-20 E. R. Williams

Latin hypercube sampling (LHS) is a widely used stratified sampling method in computer experiments. In this work, we extend the existing convergence results for the sample mean under LHS to the broader class of $Z$-estimators, estimators…

Statistics Theory · Mathematics 2026-01-09 Faouzi Hakimi

A Latin hypercuboid of order $n$ is a $d$-dimensional matrix of dimensions $n\times n\times\cdots\times n\times k$, with symbols from a set of cardinality $n$ such that each symbol occurs at most once in each axis-parallel line. If $k=n$…

Combinatorics · Mathematics 2025-02-14 Candida Bowtell , Alice Devillers , André Kündgen , Padraig Ó Catháin , Ian M. Wanless

Orthogonal array, a classical and effective tool for collecting data, has been flourished with its applications in modern computer experiments and engineering statistics. Driven by the wide use of computer experiments with both qualitative…

Methodology · Statistics 2022-03-15 Yuanzhen He , C. Devon Lin , Fasheng Sun

In this article, an adaption of an algorithm for the creation of experimental designs by Lekivetz and Jones (2015) is suggested, dealing with constraints around randomization. Split-plot design of experiments is used, when the levels of…

Methodology · Statistics 2020-03-24 Thomas Muehlenstaedt , Maria Lanzerath

The major uncertainties in studies of the multi-scale structure of the Universe arise not from observational errors but from the variety of legitimate definitions and detection methods for individual structures. To facilitate the study of…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-22 M. J. Way , P. R. Gazis , Jeffrey D. Scargle

Latin squares and hypercubes are combinatorial designs with several applications in statistics, cryptography and coding theory. In this paper, we generalize a construction of Latin squares based on bipermutive cellular automata (CA) to the…

Discrete Mathematics · Computer Science 2020-04-16 Maximilien Gadouleau , Luca Mariot

Efficient exploration of multicomponent material composition spaces is often limited by time and financial constraints, particularly when mixture and synthesis constraints exist. Traditional methods like Latin hypercube sampling (LHS)…

Computation · Statistics 2025-02-20 Christina Schenk , Maciej Haranczyk

Geographic experiments are a widely-used methodology for measuring incremental return on ad spend (iROAS) at scale, yet their design presents significant challenges. The unit count is small, heterogeneity is large, and the optimal Supergeo…

Applications · Statistics 2025-12-01 Charles Shaw

A $k$-plane of a $d$-dimensional array is a subarray formed by fixing $d-k$ coordinates and allowing the remaining $k$ coordinates to vary freely. A Latin hypercube of dimension $d$ and order $n$ is an $n\times n\times\cdots\times n$ array…

Combinatorics · Mathematics 2026-05-05 Billy Child , Ian M. Wanless

Space-filling designs are commonly used in computer experiments to fill the space of inputs so that the input-output relationship can be accurately estimated. However, in certain applications such as inverse design or feature-based…

Methodology · Statistics 2023-09-08 Shangkun Wang , Adam P. Generale , Surya R. Kalidindi , V. Roshan Joseph

A framework for designing and analyzing computer experiments is presented, which is constructed for dealing with functional and real number inputs and real number outputs. For designing experiments with both functional and real number…

Methodology · Statistics 2014-10-03 Thomas Muehlenstaedt , Jana Fruth , Olivier Roustant