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Volumn 106, Issue D13, 2001, Pages 14377-14390

Bayesian solution for nonlinear and non-Gaussian inverse problems by Markov chain Monte Carlo method

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN ANALYSIS; INVERSE PROBLEM; MARKOV CHAIN; MONTE CARLO ANALYSIS; REMOTE SENSING;

EID: 0034856846     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2001JD900007     Document Type: Article
Times cited : (48)

References (21)
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    • Brooks, S.P.1    Roberts, G.O.2
  • 5
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    • Efficient Metropolis jumping rules
    • edited by J. M. Bernardo, J. O. Berger, A. F. David, and A. F. M. Smith, Oxford Univ. Press, New York
    • Gelman, A. G., G. O. Roberts, and W. R. Gilks, Efficient Metropolis jumping rules, in Bayesian Statistics V, edited by J. M. Bernardo, J. O. Berger, A. F. David, and A. F. M. Smith, pp. 599-608, Oxford Univ. Press, New York, 1996.
    • (1996) Bayesian Statistics V , pp. 599-608
    • Gelman, A.G.1    Roberts, G.O.2    Gilks, W.R.3
  • 6
    • 0002517089 scopus 로고
    • Introducing Markov chain Monte Carlo
    • edited by W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, Chapman & Hall, New York
    • Gilks, W. R., S. Richardson, and D. J. Spiegelhalter, Introducing Markov chain Monte Carlo, in Markov Chain Monte Carlo in Practice, edited by W. R. Gilks, S. Richardson, and D. J. Spiegelhalter, pp. 1-19, Chapman & Hall, New York, 1995.
    • (1995) Markov Chain Monte Carlo in Practice , pp. 1-19
    • Gilks, W.R.1    Richardson, S.2    Spiegelhalter, D.J.3
  • 7
    • 77956889087 scopus 로고
    • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    • Green, P. J., Reversible jump Markov chain Monte Carlo computation and Bayesian model determination, Biometrica, 82, 711-732, 1995.
    • (1995) Biometrica , vol.82 , pp. 711-732
    • Green, P.J.1
  • 8
    • 0033436531 scopus 로고    scopus 로고
    • Adaptive proposal distribution for random walk Metropolis algorithm
    • Haario, H., E. Saksman, and J. Tamminen, Adaptive proposal distribution for random walk Metropolis algorithm, Comput. Stat., 14, 375-395, 1999.
    • (1999) Comput. Stat. , vol.14 , pp. 375-395
    • Haario, H.1    Saksman, E.2    Tamminen, J.3
  • 9
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov chains and their applications
    • Hastings, W., Monte Carlo sampling methods using Markov chains and their applications, Biometrica, 57, 97-109, 1970.
    • (1970) Biometrica , vol.57 , pp. 97-109
    • Hastings, W.1
  • 14
    • 0017016538 scopus 로고
    • Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation
    • Rodgers, C., Retrieval of atmospheric temperature and composition from remote measurements of thermal radiation, Rev. Geophys., 14, 609-624, 1976.
    • (1976) Rev. Geophys. , vol.14 , pp. 609-624
    • Rodgers, C.1
  • 15
    • 0025589318 scopus 로고
    • Characterization and error analysis of profiles retrieved from remote sounding measurements
    • Rodgers, G., Characterization and error analysis of profiles retrieved from remote sounding measurements, J. Geophys. Res., 95, 5587-5595, 1990.
    • (1990) J. Geophys. Res. , vol.95 , pp. 5587-5595
    • Rodgers, G.1
  • 19
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    • Markov chains for exploring posterior distributions, with discussion
    • Tierney, L., Markov chains for exploring posterior distributions, with discussion, Ann. Stat., 22, 1701-1762, 1994.
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    • Tierney, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.