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Bayesian methodsBayesian / computational

Dynamic Hamiltonian Monte Carlo

Dynamic Hamiltonian Monte Carlo — inayojulikana sana kama No-U-Turn Sampler (NUTS) — ni kiendelezi kinachobadilika cha Hamiltonian Monte Carlo ambacho huchagua kiotomatiki idadi ya hatua za ushirikiano wa leapfrog wakati wa kila mpito wa MCMC, na kuondoa hitaji la kurekebisha kigezo cha unyeti zaidi cha HMC ya kawaida. Ni kipima sampuli chaguo-msingi katika Stan na PyMC na kinafaa kwa usambazaji wa nyuma unaoendelea, unaoweza kutofautishwa wa mwelekeo wa wastani hadi wa juu.

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Vyanzo

  1. Hoffman, M. D. & Gelman, A. (2014). The No-U-Turn Sampler: Adaptively setting path lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research, 15(1), 1593–1623. link
  2. Neal, R. M. (2011). MCMC using Hamiltonian dynamics. In S. Brooks, A. Gelman, G. Jones & X.-L. Meng (Eds.), Handbook of Markov Chain Monte Carlo (pp. 113–162). CRC Press. ISBN: 978-1420079418

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Dynamic Hamiltonian Monte Carlo (No-U-Turn Sampler). ScholarGate. https://scholargate.app/sw/bayesian/dynamic-hamiltonian-monte-carlo

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ScholarGateDynamic Hamiltonian Monte Carlo (Dynamic Hamiltonian Monte Carlo (No-U-Turn Sampler)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/bayesian/dynamic-hamiltonian-monte-carlo · Seti ya data: https://doi.org/10.5281/zenodo.20539026