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Volumn 35, Issue 1, 2007, Pages 420-448

Convergence of adaptive mixtures of importance sampling schemes

Author keywords

Bayesian statistics; Kullback divergence; LLN; MCMC algorithm; Population Monte Carlo; Proposal distribution; Rao Blackwellization

Indexed keywords


EID: 49449113684     PISSN: 00905364     EISSN: None     Source Type: Journal    
DOI: 10.1214/009053606000001154     Document Type: Article
Times cited : (96)

References (25)
  • 2
    • 2442578536 scopus 로고    scopus 로고
    • Controlled Markov chain Monte Carlo methods for optimal sampling
    • Technical Report 0125, Univ. Paris Dauphine
    • ANDRIEU, C. and ROBERT, C. (2001). Controlled Markov chain Monte Carlo methods for optimal sampling. Technical Report 0125, Univ. Paris Dauphine.
    • (2001)
    • ANDRIEU, C.1    ROBERT, C.2
  • 5
    • 33646936073 scopus 로고    scopus 로고
    • Iterated importance sampling in missing data problems
    • CELEUX, G., MARIN, J. and ROBERT, C. (2006). Iterated importance sampling in missing data problems. Comput. Statist. Data Anal. 50 3386-3404.
    • (2006) Comput. Statist. Data Anal , vol.50 , pp. 3386-3404
    • CELEUX, G.1    MARIN, J.2    ROBERT, C.3
  • 6
    • 21644457738 scopus 로고    scopus 로고
    • Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference
    • CHOPIN, N. (2004). Central limit theorem for sequential Monte Carlo methods and its application to Bayesian inference. Ann. Statist. 32 2385-2411.
    • (2004) Ann. Statist , vol.32 , pp. 2385-2411
    • CHOPIN, N.1
  • 7
    • 0001560954 scopus 로고
    • Information geometry and alternating minimization procedures. Recent results in estimation theory and related topics
    • CSISZÁR, I. and TUSNÁDY, G. (1984). Information geometry and alternating minimization procedures. Recent results in estimation theory and related topics. Statist. Decisions 1984 (suppl. 1) 205-237.
    • (1984) Statist. Decisions , vol.1984 , Issue.SUPPL. 1 , pp. 205-237
    • CSISZÁR, I.1    TUSNÁDY, G.2
  • 9
    • 49449085018 scopus 로고    scopus 로고
    • Minimum variance importance sampling via population Monte Carlo
    • Technical report, Cahiers du CEREMADE, Univ. Paris Dauphine
    • DOUC, R., GUILLIN, A., MARIN, J. and ROBERT, C. (2005). Minimum variance importance sampling via population Monte Carlo. Technical report, Cahiers du CEREMADE, Univ. Paris Dauphine.
    • (2005)
    • DOUC, R.1    GUILLIN, A.2    MARIN, J.3    ROBERT, C.4
  • 10
    • 49449092253 scopus 로고    scopus 로고
    • Limit theorems for properly weighted samples with applications to sequential Monte Carlo
    • Technical report, TSI, Telecom Paris
    • DOUC, R. and MOULINES, E. (2005). Limit theorems for properly weighted samples with applications to sequential Monte Carlo. Technical report, TSI, Telecom Paris.
    • (2005)
    • DOUC, R.1    MOULINES, E.2
  • 11
    • 0003665481 scopus 로고    scopus 로고
    • DOUCET, A, DE FREITAS, N. and GORDON, N, eds, Springer, New York
    • DOUCET, A., DE FREITAS, N. and GORDON, N., eds. (2001). Sequential Monte Carlo Methods in Practice. Springer, New York.
    • (2001) Sequential Monte Carlo Methods in Practice
  • 12
    • 0032333313 scopus 로고    scopus 로고
    • Adaptive Markov chain Monte Carlo through regeneration
    • GILKS, W., ROBERTS, G. and SAHU, S. (1998). Adaptive Markov chain Monte Carlo through regeneration. J. Amer. Statist. Assoc. 93 1045-1054.
    • (1998) J. Amer. Statist. Assoc , vol.93 , pp. 1045-1054
    • GILKS, W.1    ROBERTS, G.2    SAHU, S.3
  • 13
    • 0033436531 scopus 로고    scopus 로고
    • Adaptive proposal distribution for random walk Metropolis algorithm
    • HAARIO, H., SAKSMAN, E. and TAMMINEN, J. (1999). Adaptive proposal distribution for random walk Metropolis algorithm. Comput. Statist. 14 375-395.
    • (1999) Comput. Statist , vol.14 , pp. 375-395
    • HAARIO, H.1    SAKSMAN, E.2    TAMMINEN, J.3
  • 14
    • 0038563932 scopus 로고    scopus 로고
    • An adaptive Metropolis algorithm
    • HAARIO, H., SAKSMAN, E. and TAMMINEN, J. (2001). An adaptive Metropolis algorithm. Bernoulli 7 223-242.
    • (2001) Bernoulli , vol.7 , pp. 223-242
    • HAARIO, H.1    SAKSMAN, E.2    TAMMINEN, J.3
  • 15
    • 78649424388 scopus 로고
    • Weighted average importance sampling and defensive mixture distributions
    • HESTERBERG, T. (1995). Weighted average importance sampling and defensive mixture distributions. Technometrics 37 185-194.
    • (1995) Technometrics , vol.37 , pp. 185-194
    • HESTERBERG, T.1
  • 17
    • 30344486983 scopus 로고    scopus 로고
    • Recursive Monte Carlo filters: Algorithms and theoretical analysis
    • KÜNSCH, H. (2005). Recursive Monte Carlo filters: Algorithms and theoretical analysis. Ann. Statist. 33 1983-2021.
    • (2005) Ann. Statist , vol.33 , pp. 1983-2021
    • KÜNSCH, H.1
  • 18
    • 0030551974 scopus 로고    scopus 로고
    • Rates of convergence of the Hastings and Metropolis algorithms
    • MENGERSEN, K. L. and TWEEDIE, R. L. (1996). Rates of convergence of the Hastings and Metropolis algorithms. Ann. Statist. 24 101-121.
    • (1996) Ann. Statist , vol.24 , pp. 101-121
    • MENGERSEN, K.L.1    TWEEDIE, R.L.2
  • 19
    • 0000024734 scopus 로고    scopus 로고
    • Intrinsic losses
    • ROBERT, C. (1996). Intrinsic losses. Theory and Decision 40 191-214.
    • (1996) Theory and Decision , vol.40 , pp. 191-214
    • ROBERT, C.1
  • 21
    • 0031285157 scopus 로고    scopus 로고
    • Weak convergence and optimal scaling of random walk Metropolis algorithms
    • ROBERTS, G. O., GELMAN, A. and GILKS, W. R. (1997). Weak convergence and optimal scaling of random walk Metropolis algorithms. Ann. Appl. Probab. 7 110-120.
    • (1997) Ann. Appl. Probab , vol.7 , pp. 110-120
    • ROBERTS, G.O.1    GELMAN, A.2    GILKS, W.R.3
  • 22
    • 0000458272 scopus 로고
    • Using the SIR algorithm to simulate posterior distributions
    • J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith, eds, Oxford Univ. Press
    • RUBIN, D. (1988). Using the SIR algorithm to simulate posterior distributions. In Bayesian Statistics 3 (J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith, eds.) 395-402. Oxford Univ. Press.
    • (1988) Bayesian Statistics 3 , pp. 395-402
    • RUBIN, D.1
  • 23
    • 0040916170 scopus 로고    scopus 로고
    • Adaptation for self regenerative MCMC
    • Technical report, Univ. of Wales, Cardiff
    • SAHU, S. and ZHIGLJAVSKY, A. (1998). Adaptation for self regenerative MCMC. Technical report, Univ. of Wales, Cardiff.
    • (1998)
    • SAHU, S.1    ZHIGLJAVSKY, A.2
  • 24
    • 2442470429 scopus 로고    scopus 로고
    • Self regenerative Markov chain Monte Carlo with adaptation
    • SAHU, S. and ZHIGLJAVSKY, A. (2003). Self regenerative Markov chain Monte Carlo with adaptation. Bernoulli 9 395-422.
    • (2003) Bernoulli , vol.9 , pp. 395-422
    • SAHU, S.1    ZHIGLJAVSKY, A.2
  • 25
    • 0000576595 scopus 로고
    • Markov chains for exploring posterior distributions (with discussion)
    • TIERNEY, L. (1994). Markov chains for exploring posterior distributions (with discussion). Ann. Statist. 22 1701-1762.
    • (1994) Ann. Statist , vol.22 , pp. 1701-1762
    • TIERNEY, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.