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Volumn 96, Issue 2, 2000, Pages 267-292

On simulated EM algorithms

Author keywords

EM algorithm; Incomplete data; Simulation

Indexed keywords


EID: 0012740605     PISSN: 03044076     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-4076(99)00060-3     Document Type: Article
Times cited : (11)

References (22)
  • 1
    • 0043096621 scopus 로고    scopus 로고
    • Convergence assessment techniques for Markov chain Monte Carlo
    • Brooks, S., Roberts, G., 1998. Convergence assessment techniques for Markov chain Monte Carlo. Statistics and Computing 8, 319-335.
    • (1998) Statistics and Computing , vol.8 , pp. 319-335
    • Brooks, S.1    Roberts, G.2
  • 2
    • 0002241694 scopus 로고
    • The SEM algorithm: A probabilistic teacher algorithm derived from the EM algorithm for the mixture problem
    • Celeux, G., Diebolt, J., 1985. The SEM algorithm: a probabilistic teacher algorithm derived from the EM algorithm for the mixture problem. Computational Statistics Quarterly 2, 73-82.
    • (1985) Computational Statistics Quarterly , vol.2 , pp. 73-82
    • Celeux, G.1    Diebolt, J.2
  • 3
    • 0003107701 scopus 로고    scopus 로고
    • Calculating posterior distributions and modal estimates in Markov mixture models
    • Chib, S., 1996. Calculating posterior distributions and modal estimates in Markov mixture models. Journal of Econometrics 75, 79-97.
    • (1996) Journal of Econometrics , vol.75 , pp. 79-97
    • Chib, S.1
  • 5
    • 0344601483 scopus 로고
    • Asymptotic properties of a stochastic EM algorithm for estimating mixing proportions
    • Diebolt, J., Celeux, G., 1993. Asymptotic properties of a stochastic EM algorithm for estimating mixing proportions. Communications Statistics and Stochastic Models 9, 599-613.
    • (1993) Communications Statistics and Stochastic Models , vol.9 , pp. 599-613
    • Diebolt, J.1    Celeux, G.2
  • 6
    • 0002241603 scopus 로고    scopus 로고
    • Stochastic EM: Method and application
    • Gilks, W.R., Richardson, S., Spiegelhalter, D.J. (Eds.), Chapman & Hall, London
    • Diebolt, J., Ip, E.H.S., 1996. Stochastic EM: method and application. In: Gilks, W.R., Richardson, S., Spiegelhalter, D.J. (Eds.), Markov Chain Monte Carlo in Practice. Chapman & Hall, London, pp. 259-273.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 259-273
    • Diebolt, J.1    Ip, E.H.S.2
  • 7
    • 0000247137 scopus 로고    scopus 로고
    • Estimation and optimization of functions
    • Gilks, W.R., Richardson, S., Spiegelhalter, D.J. (Eds.), Chapman & Hall, London
    • Geyer, C.J., 1996. Estimation and optimization of functions. In: Gilks, W.R., Richardson, S., Spiegelhalter, D.J. (Eds.), Markov Chain Monte Carlo in Practice. Chapman & Hall, London, pp. 241-258.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 241-258
    • Geyer, C.J.1
  • 11
    • 0001702994 scopus 로고
    • A contraction principle for certain Markov chains and its applications
    • Letac, G., 1986. A contraction principle for certain Markov chains and its applications. Contemporary Mathematics 50, 263-273.
    • (1986) Contemporary Mathematics , vol.50 , pp. 263-273
    • Letac, G.1
  • 14
    • 84864615423 scopus 로고
    • Using EM to obtain asymptotic variance-covariance matrices: The SEM algorithm
    • Meng, X.-L., Rubin, D.B., 1991. Using EM to obtain asymptotic variance-covariance matrices: the SEM algorithm. Journal of the American Statistical Association 86, 899-909.
    • (1991) Journal of the American Statistical Association , vol.86 , pp. 899-909
    • Meng, X.-L.1    Rubin, D.B.2
  • 16
    • 0001331135 scopus 로고
    • Simulation and the asymptotics of optimization estimators
    • Pakes, A., Pollard, D., 1989. Simulation and the asymptotics of optimization estimators. Econometrica 57, 1027-1057.
    • (1989) Econometrica , vol.57 , pp. 1027-1057
    • Pakes, A.1    Pollard, D.2
  • 17
    • 0000759236 scopus 로고
    • How many iterations in the Gibbs sampler?
    • Bernardo, J.M., Berger, J.O., Dawid A.P., Smith, A.F.M. (Eds.), Oxford University Press, Oxford
    • Raftery, A.E., Lewis, S.M., 1992. How many iterations in the Gibbs sampler? In: Bernardo, J.M., Berger, J.O., Dawid A.P., Smith, A.F.M. (Eds.), Bayesian Statistics, Vol. 4. Oxford University Press, Oxford, pp. 763-773.
    • (1992) Bayesian Statistics , vol.4 , pp. 763-773
    • Raftery, A.E.1    Lewis, S.M.2
  • 18
    • 0000672899 scopus 로고
    • Extensions of estimation methods using the EM algorithm
    • Ruud, P.A., 1991. Extensions of estimation methods using the EM algorithm. Journal of Econometrics 49, 305-341.
    • (1991) Journal of Econometrics , vol.49 , pp. 305-341
    • Ruud, P.A.1
  • 19
    • 0007071163 scopus 로고
    • Asymptotic results for multiple imputation
    • Schenker, N., Welsh, A.H., 1988. Asymptotic results for multiple imputation. Annals of Statistics 16, 1550-1566.
    • (1988) Annals of Statistics , vol.16 , pp. 1550-1566
    • Schenker, N.1    Welsh, A.H.2
  • 20
    • 0001953676 scopus 로고
    • ML theory for incomplete data from an exponential family
    • Sundberg, R., 1971. ML theory for incomplete data from an exponential family. Scandinavian Journal of Statistics 1, 49-58.
    • (1971) Scandinavian Journal of Statistics , vol.1 , pp. 49-58
    • Sundberg, R.1
  • 21
    • 84950432017 scopus 로고
    • A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms
    • Wei, G.C.G., 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
  • 22
    • 0002210265 scopus 로고
    • 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. 7
    • (1983) Annals of Statistics , vol.11 , pp. 95-1037
    • Wu, C.F.J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.