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Simulacija pokretanja×Simulacija Monte Carlo×
PodručjeSimulacijaDonošenje odluka
ObiteljProcess / pipelineMCDM
Godina nastanka19791949
TvoracBradley EfronMetropolis, N., Ulam, S.
VrstaSimulation-based nonparametric inferenceRobustness wrapper — Monte Carlo uncertainty propagation
Temeljni izvorEfron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC. DOI ↗Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗
Drugi nazivibootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling)
Srodne50
SažetakBootstrap simulation, introduced by Bradley Efron in 1979, is a simulation-based inference method that derives the sampling distribution of virtually any statistic by repeatedly resampling with replacement from the observed data. Because it requires no parametric distributional assumptions, it provides a robust, general-purpose alternative to analytical confidence intervals and parametric hypothesis tests across continuous, ordinal, binary, and count data.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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ScholarGateUsporedite metode: Bootstrap Simulation · MONTE-CARLO-SIMULATION. Preuzeto 2026-06-15 s https://scholargate.app/hr/compare