Comparer des méthodes

	Échantillonnage par hypercube latin	Planification d'Expériences
Domaine	Simulation	Plans d'expériences
Famille	Process / pipeline	Process / pipeline
Année d'origine	1979	1935
Auteur d'origine	—	Ronald A. Fisher
Type	Stratified space-filling sampling design	Experimental planning framework
Source fondatrice	McKay, M.D., Beckman, R.J. & Conover, W.J. (1979). A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output from a Computer Code. Technometrics, 21(2), 239-245.	Fisher, R. A. (1935). The Design of Experiments. Oliver and Boyd.
Alias	LHS, Latin Hiperküp Örnekleme (LHS) ve Duyarlılık Analizi, stratified sampling design, space-filling design	DOE, experimental design, factorial experimentation, planned experimentation
Apparentées	4	3
Résumé	Latin Hypercube Sampling (LHS) is a stratified space-filling design for computer experiments, introduced by McKay, Beckman, and Conover in 1979. It divides each input variable's range into equally probable strata and draws exactly one sample per stratum, ensuring that the full input space is covered with far fewer model evaluations than standard Monte Carlo simulation requires. It is routinely paired with global sensitivity analysis — particularly Sobol indices — to quantify how much each input drives output variability.	Design of Experiments (DOE) is a systematic framework for planning, conducting, and analyzing controlled experiments to determine how multiple input factors simultaneously affect one or more responses. Introduced by Ronald A. Fisher in 1935, DOE allows researchers and engineers to identify causal relationships, quantify factor effects, and find optimal settings efficiently — using far fewer runs than one-factor-at-a-time approaches. It is foundational in engineering, manufacturing, agriculture, and applied sciences.