विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| लैटिन हाइपरक्यूब सैंपलिंग× | मोंटे कार्लो सिमुलेशन× | |
|---|---|---|
| क्षेत्र≠ | अनुकरण | निर्णयन |
| परिवार≠ | Process / pipeline | MCDM |
| उद्भव वर्ष≠ | 1979 | 1949 |
| प्रवर्तक≠ | — | Metropolis, N., Ulam, S. |
| प्रकार≠ | Stratified space-filling sampling design | Robustness wrapper — Monte Carlo uncertainty propagation |
| मौलिक स्रोत≠ | 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 ↗ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ |
| उपनाम≠ | LHS, Latin Hiperküp Örnekleme (LHS) ve Duyarlılık Analizi, stratified sampling design, space-filling design | — |
| संबंधित≠ | 4 | 0 |
| सारांश≠ | 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. | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
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