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Volumn 21, Issue 4, 2011, Pages 649-656

Diffusive nested sampling

Author keywords

Bayesian computation; Markov chain Monte Carlo; Nested sampling

Indexed keywords


EID: 80051472308     PISSN: 09603174     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11222-010-9198-8     Document Type: Article
Times cited : (158)

References (13)
  • 1
    • 75149191785 scopus 로고    scopus 로고
    • Tailored randomized-block MCMC methods with application to DSGE models
    • Chib, S., Ramamurthy, S.: Tailored randomized-block MCMC methods with application to DSGE models. J. Econom. 155, 19-38 (2010).
    • (2010) J. Econom. , vol.155 , pp. 19-38
    • Chib, S.1    Ramamurthy, S.2
  • 3
    • 33644899039 scopus 로고
    • Simulated tempering: a new Monte Carlo scheme
    • Marinari, E., Parisi, G.: Simulated tempering: a new Monte Carlo scheme. Europhys. Lett. 19, 451 (1992).
    • (1992) Europhys. Lett. , vol.19 , pp. 451
    • Marinari, E.1    Parisi, G.2
  • 4
    • 33644772615 scopus 로고    scopus 로고
    • A nested sampling algorithm for cosmological model selection
    • Mukherjee, P., Parkinson, D., Liddle, A. R.: A nested sampling algorithm for cosmological model selection. Astrophys. J. 638, L51-L54 (2006).
    • (2006) Astrophys. J. , vol.638 , pp. 51-54
    • Mukherjee, P.1    Parkinson, D.2    Liddle, A.R.3
  • 5
    • 59849083255 scopus 로고    scopus 로고
    • PhD thesis, Gatsby computational neuroscience unit, University College London
    • Murray, I.: Advances in Markov chain Monte Carlo methods. PhD thesis, Gatsby computational neuroscience unit, University College London (2007).
    • (2007) Advances in Markov chain Monte Carlo methods
    • Murray, I.1
  • 6
    • 1642370803 scopus 로고    scopus 로고
    • Slice sampling (with discussion)
    • Neal, R. M.: Slice sampling (with discussion). Ann. Stat. 31, 705-767 (2003).
    • (2003) Ann. Stat. , vol.31 , pp. 705-767
    • Neal, R.M.1
  • 7
    • 77955565010 scopus 로고    scopus 로고
    • Efficient sampling of atomic configurational spaces
    • Pártay, L. B., Bartók, A. P., Csányi, G.: Efficient sampling of atomic configurational spaces. J. Phys. Chem. B 114(32), 10502-10512 (2010).
    • (2010) J. Phys. Chem. B , vol.114 , Issue.32 , pp. 10502-10512
    • Pártay, L.B.1    Bartók, A.P.2    Csányi, G.3
  • 8
    • 0031285157 scopus 로고    scopus 로고
    • Weak convergence and optimal scaling of random walk Metropolis algorithms
    • Roberts, G. O., Gelman, A., Gilks, W. R.: Weak convergence and optimal scaling of random walk Metropolis algorithms. Ann. Appl. Probab. 7(1), 110-120 (1997).
    • (1997) Ann. Appl. Probab. , vol.7 , Issue.1 , pp. 110-120
    • Roberts, G.O.1    Gelman, A.2    Gilks, W.R.3
  • 9
    • 84863994792 scopus 로고    scopus 로고
    • Optimal proposal distributions and adaptive MCMC
    • S. P. Brooks, A. Gelman, G. Jones, and X.-L. Meng (Eds.), Boca Raton: Chapman and Hall/CRC Press
    • Rosenthal, J. S.: Optimal proposal distributions and adaptive MCMC. In: Brooks, S. P., Gelman, A., Jones, G., Meng, X.-L. (eds.) Handbook of Markov Chain Monte Carlo. Chapman and Hall/CRC Press, Boca Raton (2010).
    • (2010) Handbook of Markov Chain Monte Carlo
    • Rosenthal, J.S.1
  • 11
    • 35148901361 scopus 로고    scopus 로고
    • Nested sampling for general Bayesian computation
    • Skilling, J.: Nested sampling for general Bayesian computation. Bayesian Anal. 4, 833-860 (2006).
    • (2006) Bayesian Anal. , vol.4 , pp. 833-860
    • Skilling, J.1
  • 13
    • 6644221271 scopus 로고    scopus 로고
    • Efficient, multiple-range random walk algorithm to calculate the density of states
    • Wang, F., Landau, D. P.: Efficient, multiple-range random walk algorithm to calculate the density of states. Phys. Rev. Lett. 86, 2050 (2001).
    • (2001) Phys. Rev. Lett. , vol.86 , pp. 2050
    • Wang, F.1    Landau, D.P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.