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Anàlisi de Sensibilitat Global×Mostreig d'Hipercub Llatí×
CampSimulacióSimulació
FamíliaProcess / pipelineProcess / pipeline
Any d'origen1973–20011979
Autor originalI.M. Sobol (indices, 2001); Morris (screening, 1991); Cukier et al. (FAST, 1973)
TipusVariance-based sensitivity decompositionStratified space-filling sampling design
Font seminalSobol, I.M. (2001). Global Sensitivity Indices for Nonlinear Mathematical Models and Their Monte Carlo Estimates. Mathematics and Computers in Simulation, 55(1–3), 271–280. DOI ↗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. DOI ↗
Àliesvariance decomposition, Sobol indices, Morris screening, FAST methodLHS, Latin Hiperküp Örnekleme (LHS) ve Duyarlılık Analizi, stratified sampling design, space-filling design
Relacionats44
ResumGlobal sensitivity analysis (GSA) is a family of techniques that decompose the variance of a model's output across its input parameters, quantifying how much each input — and each combination of inputs — contributes to the total uncertainty in the result. Sobol's variance-based indices (2001), Morris's one-at-a-time (OAT) screening (1991), and the Fourier Amplitude Sensitivity Test (FAST, first proposed by Cukier et al. in 1973) are the three most widely used approaches. Together they serve as the standard toolkit for identifying which parameters drive model behaviour and which can be safely fixed.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.
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ScholarGateCompara mètodes: Global Sensitivity Analysis · Latin Hypercube Sampling. Recuperat el 2026-06-15 de https://scholargate.app/ca/compare