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Journal Abstract Search

160 related items for PubMed ID: 24653788

  • 1. Bayesian Analysis for Exponential Random Graph Models Using the Adaptive Exchange Sampler.
    Jin IH, Yuan Y, Liang F.
    Stat Interface; 2013 Oct 01; 6(4):559-576. PubMed ID: 24653788
    [Abstract] [Full Text] [Related]

  • 2. A Monte Carlo Metropolis-Hastings algorithm for sampling from distributions with intractable normalizing constants.
    Liang F, Jin IH.
    Neural Comput; 2013 Aug 01; 25(8):2199-234. PubMed ID: 23607562
    [Abstract] [Full Text] [Related]

  • 3. Bayesian adaptive Markov chain Monte Carlo estimation of genetic parameters.
    Mathew B, Bauer AM, Koistinen P, Reetz TC, Léon J, Sillanpää MJ.
    Heredity (Edinb); 2012 Oct 01; 109(4):235-45. PubMed ID: 22805656
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  • 5. Highly scalable maximum likelihood and conjugate Bayesian inference for ERGMs on graph sets with equivalent vertices.
    Yin F, Butts CT.
    PLoS One; 2022 Oct 01; 17(8):e0273039. PubMed ID: 36018834
    [Abstract] [Full Text] [Related]

  • 6. Inference of regulatory networks with a convergence improved MCMC sampler.
    Agostinho NB, Machado KS, Werhli AV.
    BMC Bioinformatics; 2015 Sep 24; 16():306. PubMed ID: 26399857
    [Abstract] [Full Text] [Related]

  • 7. A Novel Simulation Method for Binary Discrete Exponential Families, with Application to Social Networks.
    Butts CT.
    J Math Sociol; 2015 Sep 24; 39(3):174-202. PubMed ID: 26586920
    [Abstract] [Full Text] [Related]

  • 8. Bayesian exponential random graph modelling of interhospital patient referral networks.
    Caimo A, Pallotti F, Lomi A.
    Stat Med; 2017 Aug 15; 36(18):2902-2920. PubMed ID: 28421624
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  • 10. Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals.
    Brofos JA, Gabrié M, Brubaker MA, Lederman RR.
    Proc Mach Learn Res; 2022 Mar 15; 151():5949-5986. PubMed ID: 36789101
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  • 12. MCMC estimation for the p(2) network regression model with crossed random effects.
    Zijlstra BJ, van Duijn MA, Snijders TA.
    Br J Math Stat Psychol; 2009 Feb 15; 62(Pt 1):143-66. PubMed ID: 19208289
    [Abstract] [Full Text] [Related]

  • 13. Assessing the convergence of Markov Chain Monte Carlo methods: an example from evaluation of diagnostic tests in absence of a gold standard.
    Toft N, Innocent GT, Gettinby G, Reid SW.
    Prev Vet Med; 2007 May 16; 79(2-4):244-56. PubMed ID: 17292499
    [Abstract] [Full Text] [Related]

  • 14. Adaptive Markov chain Monte Carlo for auxiliary variable method and its application to parallel tempering.
    Araki T, Ikeda K.
    Neural Netw; 2013 Jul 16; 43():33-40. PubMed ID: 23500498
    [Abstract] [Full Text] [Related]

  • 15. Fast genomic prediction of breeding values using parallel Markov chain Monte Carlo with convergence diagnosis.
    Guo P, Zhu B, Niu H, Wang Z, Liang Y, Chen Y, Zhang L, Ni H, Guo Y, Hay EHA, Gao X, Gao H, Wu X, Xu L, Li J.
    BMC Bioinformatics; 2018 Jan 03; 19(1):3. PubMed ID: 29298666
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  • 17. Estimating the granularity coefficient of a Potts-Markov random field within a Markov chain Monte Carlo algorithm.
    Pereyra M, Dobigeon N, Batatia H, Tourneret JY.
    IEEE Trans Image Process; 2013 Jun 03; 22(6):2385-97. PubMed ID: 23475357
    [Abstract] [Full Text] [Related]

  • 18. A general construction for parallelizing Metropolis-Hastings algorithms.
    Calderhead B.
    Proc Natl Acad Sci U S A; 2014 Dec 09; 111(49):17408-13. PubMed ID: 25422442
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  • 20. A curved exponential family model for complex networks.
    Handcock MS, Morris M.
    Comput Math Organ Theory; 2009 Dec 01; 15(4):294-302. PubMed ID: 26612976
    [Abstract] [Full Text] [Related]

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