השוואת שיטות

	סימולציית מונטה קרלו דינמית	סימולציית Bootstrap
תחום	בייסיאני	סימולציה
משפחה	Bayesian methods	Process / pipeline
שנת המקור	1975–1977	1979
הוגה השיטה	Bortz, Kalos & Lebowitz (physics); Gillespie (chemistry)	Bradley Efron
סוג	stochastic simulation	Simulation-based nonparametric inference
מקור מכונן	Bortz, 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.	Efron, B. & Tibshirani, R.J. (1993). An Introduction to the Bootstrap. Chapman & Hall/CRC.
כינויים	DMC simulation, kinetic Monte Carlo, time-driven Monte Carlo, event-driven Monte Carlo	bootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling)
קשורות	6	5
תקציר	Dynamic 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.