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Volumn 74, Issue 5, 2004, Pages 349-360

An automated (Markov chain) Monte Carlo EM algorithm

Author keywords

Generalized linear mixed models; Gibbs sampler; Importance sampling; Metropolis Hastings algorithm; Regenerative simulation; Renewal theory

Indexed keywords


EID: 2442599184     PISSN: 00949655     EISSN: None     Source Type: Journal    
DOI: 10.1080/0094965031000147704     Document Type: Article
Times cited : (30)

References (17)
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  • 2
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    • Chan, J.S.K.1    Kuk, A.Y.C.2
  • 3
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    • Discussion of "Markov Chains for exploring posterior distributions"
    • Chan, K. S. and Geyer, C. (1994). Discussion of "Markov Chains for exploring posterior distributions". The Annals of Statistics, 22(4), 1747-1758.
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    • Chan, K.S.1    Geyer, C.2
  • 7
    • 0031479575 scopus 로고    scopus 로고
    • Maximum likelihood algorithms for generalized linear mixed models
    • McCulloch, C. E. (1997). Maximum likelihood algorithms for generalized linear mixed models. Journal of the American Statistical Association, 92, 162-170.
    • (1997) Journal of the American Statistical Association , vol.92 , pp. 162-170
    • McCulloch, C.E.1
  • 8
    • 21344497135 scopus 로고
    • Maximum likelihood variance components estimation for binary data
    • McCulloch, C. E. (1994). Maximum likelihood variance components estimation for binary data. Journal of the American Statistical Association, 89, 330-335.
    • (1994) Journal of the American Statistical Association , vol.89 , pp. 330-335
    • McCulloch, C.E.1
  • 10
    • 0033076076 scopus 로고    scopus 로고
    • Monte Carlo EM with importance reweighting and its applications to random effects models
    • Quintana, F. A., Liu, J. S. and del Pino, G. E. (1999). Monte Carlo EM with importance reweighting and its applications to random effects models. Computational Statistics and Data Analysis, 29, 429-444.
    • (1999) Computational Statistics and Data Analysis , vol.29 , pp. 429-444
    • Quintana, F.A.1    Liu, J.S.2    Del Pino, G.E.3
  • 11
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    • Simulation of truncated normal variables
    • Robert, C. P. (1995). Simulation of truncated normal variables. Statistics and Computing, 5, 121-125.
    • (1995) Statistics and Computing , vol.5 , pp. 121-125
    • Robert, C.P.1
  • 15
    • 84950432017 scopus 로고
    • A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms
    • Wei, G. C. G. and Tanner, M. A. (1990). A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms. Journal of the American Statistical Association, 85, 699-704.
    • (1990) Journal of the American Statistical Association , vol.85 , pp. 699-704
    • Wei, G.C.G.1    Tanner, M.A.2
  • 16
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    • On the convergence properties of the EM algorithm
    • Wu, C. F. J. (1983). On the convergence properties of the EM algorithm. Annals of Statistics, 11, 95-103.
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  • 17
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    • Nesting EM algorithms for computational efficiency
    • van Dyk, D. (2000). Nesting EM algorithms for computational efficiency. Statistica Sinica, 10, 203-225.
    • (2000) Statistica Sinica , vol.10 , pp. 203-225
    • Van Dyk, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.