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Uiguzi wa Monte Carlo wa Bayesian — Sampuli za kiholela zilizo na taarifa za awali kwa ajili ya uhakiki wa kutokuwa na uhakika

Uiguzi wa Monte Carlo wa Bayesian huunganisha uhakiki wa takwimu wa Bayesian na sampuli za Monte Carlo ili kusambaza kutokuwa na uhakika kupitia mifumo changamano. Badala ya kutoa sampuli kutoka kwa usambazaji wa kiholela, huweka masharti ya sampuli kwa data zilizozingatiwa na maarifa ya awali ya kitaalamu kupitia nadharia ya Bayes, ikitoa makadirio ya kutokuwa na uhakika yanayotokana na hali ya baadaye ambayo yana maelewano ya kitabia na yanaeleweka kwa maneno ya uwezekano.

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Vyanzo

  1. O'Hagan, A., Buck, C. E., Daneshkhah, A., Eiser, J. R., Garthwaite, P. H., Jenkinson, D. J., Oakley, J. E., & Rakow, T. (2006). Uncertain Judgements: Eliciting Experts' Probabilities. Wiley. ISBN: 9780470029992
  2. O'Hagan, A. (1987). Monte Carlo is fundamentally unsound. The Statistician, 36(2-3), 247-249. DOI: 10.2307/2348519

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Bayesian Monte Carlo Simulation — Prior-informed stochastic sampling for uncertainty quantification. ScholarGate. https://scholargate.app/sw/simulation/bayesian-monte-carlo-simulation

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Imerejelewa na

ScholarGateBayesian Monte Carlo Simulation (Bayesian Monte Carlo Simulation — Prior-informed stochastic sampling for uncertainty quantification). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/simulation/bayesian-monte-carlo-simulation · Seti ya data: https://doi.org/10.5281/zenodo.20539026