Markov Chain Monte Carlo (MCMC)
Markov Chain Monte Carlo (MCMC) ni familia ya algoriti za kikokotoo za sampuli kutoka kwa usambazaji wa uwezekano tata, mara nyingi zaidi usambazaji wa nyuma unaojitokeza katika ubashiri wa Bayesian. Badala ya kukokotoa nyuma kwa njia ya uchanganuzi—ambayo mara chache huwezekana kwa miundo ya kweli—MCMC huunda mnyororo wa Markov ambao usambazaji wake tuli ni usambazaji lengwa na huchota sampuli tegemezi kutoka kwake, kuwezesha ubashiri kamili wa uwezekano kwa karibu mfumo wowote.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
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Vyanzo
- Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955
- Brooks, S., Gelman, A., Jones, G. & Meng, X.-L. (Eds.). (2011). Handbook of Markov Chain Monte Carlo. CRC Press. ISBN: 978-1420079418
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 1). Markov Chain Monte Carlo. ScholarGate. https://scholargate.app/sw/bayesian/mcmc
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Bayesian Model AveragingMbinu za Bayes↔ compare
- Usajili wa BayesianMbinu za Bayes↔ compare
- Utoaji wa KigezoMbinu za Bayes↔ compare
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