Comparar métodos

	Latin Hypercube Sampling	Desenho de Experimentos
Área	Simulação	Delineamento experimental
Família	Process / pipeline	Process / pipeline
Ano de origem	1979	1935
Autor original	—	Ronald A. Fisher
Tipo	Stratified space-filling sampling design	Experimental planning framework
Fonte seminal	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.
Outros nomes	LHS, Latin Hiperküp Örnekleme (LHS) ve Duyarlılık Analizi, stratified sampling design, space-filling design	DOE, experimental design, factorial experimentation, planned experimentation
Relacionados	4	3
Resumo	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.