Algoriti ya Metropolis-Hastings
Algoriti ya Metropolis-Hastings (MH) ni mbinu ya jumla ya mnyororo wa Markov Monte Carlo (MCMC) kwa ajili ya kupata sampuli kutoka kwa usambazaji wowote wa uwezekano ambao msongamano wake unaweza kutathminiwa hadi kwa kiwango cha kawaida. Ilianzishwa na Metropolis, Rosenbluth, Rosenbluth, Teller, na Teller (1953) katika fizikia ya kompyuta na kuendelezwa na Hastings (1970) kwa usambazaji wa mapendekezo yasiyo sawia, ni algoriti ya msingi ambayo karibu sampula zote za baadaye za MCMC — sampuli ya Gibbs, Hamiltonian Monte Carlo, sampuli ya mchoro — zinatokana au zinaweza kuonekana kama visa maalum.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
+2 more
Vyanzo
- Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953). Equation of state calculations by fast computing machines. The Journal of Chemical Physics, 21(6), 1087–1092. DOI: 10.1063/1.1699114 ↗
- Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1), 97–109. DOI: 10.1093/biomet/57.1.97 ↗
- Robert, C. P., & Casella, G. (2004). Monte Carlo Statistical Methods (2nd ed.). Springer. ISBN: 978-0-387-21239-5
- 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: 978-1-439-84095-5
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Metropolis-Hastings Markov Chain Monte Carlo Algorithm. ScholarGate. https://scholargate.app/sw/bayesian/metropolis-hastings-algorithm
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.
- Usajili wa BayesianMbinu za Bayes↔ compare
- Sampuli ya GibbsMbinu za Bayes↔ compare
- Hamiltonian Monte CarloMbinu za Bayes↔ compare
- Monte Carlo SekwenshialiMbinu za Bayes↔ compare
- Uchujaji wa vipande (Slice Sampling)Mbinu za Bayes↔ compare
Imerejelewa na
Umeona tatizo kwenye ukurasa huu? Ripoti au pendekeza marekebisho →