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क्षेत्रअनुकरणनिर्णयन
परिवारProcess / pipelineMCDM
उद्भव वर्ष19791949
प्रवर्तकBradley EfronMetropolis, N., Ulam, S.
प्रकारSimulation-based nonparametric inferenceRobustness wrapper — Monte Carlo uncertainty propagation
मौलिक स्रोतEfron, 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 ↗
उपनामbootstrap resampling, empirical resampling, nonparametric bootstrap, Önyükleme Simülasyonu (Bootstrap Resampling)
संबंधित50
सारांशBootstrap 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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ScholarGateविधियों की तुलना करें: Bootstrap Simulation · MONTE-CARLO-SIMULATION. 2026-06-17 को यहाँ से प्राप्त https://scholargate.app/hi/compare