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محاكاة مونت كارلو الديناميكية×محاكاة التمهيد×
المجالبايزيالمحاكاة
العائلةBayesian methodsProcess / pipeline
سنة النشأة1975–19771979
صاحب الطريقةBortz, Kalos & Lebowitz (physics); Gillespie (chemistry)Bradley Efron
النوعstochastic simulationSimulation-based nonparametric inference
المصدر التأسيسيBortz, A. B., Kalos, M. H., & Lebowitz, J. L. (1975). A new algorithm for Monte Carlo simulation of Ising spin systems. Journal of Computational Physics, 17(1), 10–18. DOI ↗Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC. DOI ↗
الأسماء البديلةDMC simulation, kinetic Monte Carlo, time-driven Monte Carlo, event-driven Monte Carlobootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling)
ذات صلة65
الملخصDynamic Monte Carlo (DMC) simulation is a computational method that tracks the stochastic time evolution of a system by drawing random event sequences weighted by transition rates. Unlike static Monte Carlo sampling of equilibrium distributions, DMC explicitly advances a clock, making it suitable for kinetic, reaction, and time-dependent phenomena where the sequence and timing of events matter.Bootstrap 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.
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ScholarGateقارن الطرق: Dynamic Monte Carlo Simulation · Bootstrap Simulation. استُرجع بتاريخ 2026-06-15 من https://scholargate.app/ar/compare