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Bayesian methodsBayesian / computational

Markov Chain Monte Carlo Imara

MCMC Imara inachanganya usampulishaji wa Markov Chain Monte Carlo na mbinu za uimara ili kutoa hitimisho la baada ya uchunguzi la kuaminika wakati data ina "outliers", wakati modeli iliyodhaniwa haijaainishwa vizuri, au wakati usambazaji lengwa una mikia mizito inayosababisha visampulishaji vya kawaida kuchanganyika vibaya au kutoa makadirio potofu.

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Vyanzo

  1. Roberts, G. O. & Rosenthal, J. S. (2004). General state space Markov chains and MCMC algorithms. Probability Surveys, 1, 20–71. DOI: 10.1214/154957804100000024
  2. Barp, A., Kennedy, C., Durmus, A. & Girolami, M. (2022). Targeted separation and convergence with kernel discrepancies. arXiv preprint. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Robust Markov Chain Monte Carlo Sampling. ScholarGate. https://scholargate.app/sw/bayesian/robust-markov-chain-monte-carlo

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Imerejelewa na

ScholarGateRobust Markov chain Monte Carlo (Robust Markov Chain Monte Carlo Sampling). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/bayesian/robust-markov-chain-monte-carlo · Seti ya data: https://doi.org/10.5281/zenodo.20539026