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Bayesian methodsBayesian / computational

Sampuli ya Gibbs

Sampuli ya Gibbs ni algoriti ya mnyororo wa Markov Monte Carlo ambayo inakadiria usambazaji wa nyuma wa vipimo vingi kwa kuchora mara kwa mara kila kigezo kutoka kwa usambazaji wake kamili wa masharti kulingana na vigezo vingine vyote na data. Kwa sababu kila kuchora ni kamili kutoka kwa masharti — sio pendekezo ambalo linaweza kukataliwa — sampula ni yenye ufanisi wakati masharti hayo yanapatikana kwa fomu iliyofungwa.

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Vyanzo

  1. Geman, S. & Geman, D. (1984). Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 6(6), 721-741. DOI: 10.1109/TPAMI.1984.4767596
  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). Gibbs Sampling Markov Chain Monte Carlo. ScholarGate. https://scholargate.app/sw/bayesian/gibbs-sampling

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Imerejelewa na

ScholarGateGibbs Sampling (Gibbs Sampling Markov Chain Monte Carlo). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/bayesian/gibbs-sampling · Seti ya data: https://doi.org/10.5281/zenodo.20539026