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Bayesian methodsBayesian / computational

MCMC ya Ngazi Nyingi

MCMC ya Ngazi Nyingi inatumia sampuli ya Markov chain Monte Carlo kwa mifano ya Bayesian yenye ngazi (multilevel). Inachota sampuli kutoka kwa posterior ya pamoja ya vigezo vya ngazi ya kikundi na ngazi ya idadi ya watu kwa wakati mmoja, ikisambaza kutokuwa na uhakika katika ngazi zote na kuwezesha hitimisho katika miundo ya data iliyokusanywa au iliyowekwa ndani ambapo uchunguzi ndani ya vikundi unashiriki sifa za usambazaji zinazofanana.

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Vyanzo

  1. 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
  2. Gelfand, A. E. & Smith, A. F. M. (1990). Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association, 85(410), 398-409. DOI: 10.1080/01621459.1990.10476213

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Multilevel Markov Chain Monte Carlo. ScholarGate. https://scholargate.app/sw/bayesian/multilevel-mcmc

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Imerejelewa na

ScholarGateMultilevel MCMC (Multilevel Markov Chain Monte Carlo). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/bayesian/multilevel-mcmc · Seti ya data: https://doi.org/10.5281/zenodo.20539026