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Volumn 54, Issue 3, 2010, Pages 688-697

Distributed evolutionary Monte Carlo for Bayesian computing

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN; BAYESIAN ANALYSIS; DATA EXAMPLES; DISTRIBUTED GENETIC ALGORITHMS; GENETIC OPERATORS; HIGH-DIMENSIONAL; MARKOV CHAIN; MARKOV CHAIN MONTE CARLO; MARKOV CHAIN MONTE CARLO ALGORITHMS; MONTE CARLO; MULTI-MODAL; MULTIMODAL DISTRIBUTIONS; STATIONARY DISTRIBUTION; TARGET FUNCTIONS;

EID: 70549107421     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csda.2008.10.025     Document Type: Article
Times cited : (15)

References (23)
  • 1
    • 0000308566 scopus 로고
    • Rawlins G.J.E. (Ed), Morgan Kaufmann, San Mateo, CA
    • Eshelman L.J., and Schaffer J.D. Real-Coded Genetic Algorithm and Interval-Schematai. In: Rawlins G.J.E. (Ed). Foundation Genetic Algorithms vol. 2 (1993), Morgan Kaufmann, San Mateo, CA 187-202
    • (1993) Foundation Genetic Algorithms , vol.2 , pp. 187-202
    • Eshelman, L.J.1    Schaffer, J.D.2
  • 2
    • 0344521704 scopus 로고    scopus 로고
    • Bernardo J.M., Berger J.O., Dawid A.P., and Smith A.F.M. (Eds), Oxford University Press, New York
    • Gelman S., Roberts R.O., and Gilks W.R. Efficient Metropolis Jumping Rules. In: Bernardo J.M., Berger J.O., Dawid A.P., and Smith A.F.M. (Eds). Bayesian Statistics vol. 5 (1996), Oxford University Press, New York
    • (1996) Bayesian Statistics , vol.5
    • Gelman, S.1    Roberts, R.O.2    Gilks, W.R.3
  • 7
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov Chains and their applications
    • Hastings W.K. Monte Carlo sampling methods using Markov Chains and their applications. Biometrika 57 (1970) 97-109
    • (1970) Biometrika , vol.57 , pp. 97-109
    • Hastings, W.K.1
  • 9
    • 0030516672 scopus 로고    scopus 로고
    • Exchange Monte Carlo method and application to spin class simulations
    • Hukushima K., and Nemeto K. Exchange Monte Carlo method and application to spin class simulations. J. Phys. Soc Japan. 65 (1996) 1604-1608
    • (1996) J. Phys. Soc Japan. , vol.65 , pp. 1604-1608
    • Hukushima, K.1    Nemeto, K.2
  • 11
    • 0037266164 scopus 로고    scopus 로고
    • Population Markov Chain Monte Carlo
    • Laskey K.B., and Myers J.W. Population Markov Chain Monte Carlo. Machine Learning 50 (2003) 175-196
    • (2003) Machine Learning , vol.50 , pp. 175-196
    • Laskey, K.B.1    Myers, J.W.2
  • 12
    • 0034403006 scopus 로고    scopus 로고
    • p model sampling and change point problem
    • p model sampling and change point problem. Statist. Sinica. 10 (2000) 317-342
    • (2000) Statist. Sinica. , vol.10 , pp. 317-342
    • Liang, F.1    Wong, W.H.2
  • 13
    • 1542573405 scopus 로고    scopus 로고
    • Real-parameter evolutionary Monte Carlo with applications to Bayesian mixture models
    • Liang F., and Wong W.H. Real-parameter evolutionary Monte Carlo with applications to Bayesian mixture models. J. Amer. Statist. Assoc. 96 (2001) 653-666
    • (2001) J. Amer. Statist. Assoc. , vol.96 , pp. 653-666
    • Liang, F.1    Wong, W.H.2
  • 14
    • 0442309554 scopus 로고    scopus 로고
    • The multiple-try method and local optimization in metropolis sampling
    • Liu S.J., Liang F., and Wong W.H. The multiple-try method and local optimization in metropolis sampling. J. Amer. Statist. Assoc. 95 (2000) 121-134
    • (2000) J. Amer. Statist. Assoc. , vol.95 , pp. 121-134
    • Liu, S.J.1    Liang, F.2    Wong, W.H.3
  • 16
    • 0003066726 scopus 로고    scopus 로고
    • A real-coded genetic algorithm for function optimization using unimodal normal distribution crossover
    • Ono, I., Kobayashi, S., 1997. A real-coded genetic algorithm for function optimization using unimodal normal distribution crossover. in: Proc. 7th International Conference on Genetic Algorithms. pp. 246-253
    • (1997) Proc. 7th International Conference on Genetic Algorithms , pp. 246-253
    • Ono, I.1    Kobayashi, S.2
  • 17
    • 0000940729 scopus 로고
    • Facilitating the Gibbs sampler: The Gibbs stopper and the Griddy-Gibbs sampler
    • Ritter C., and Tanner M.A. Facilitating the Gibbs sampler: The Gibbs stopper and the Griddy-Gibbs sampler. J. Amer. Statist. Assoc. 87 (1992) 861-868
    • (1992) J. Amer. Statist. Assoc. , vol.87 , pp. 861-868
    • Ritter, C.1    Tanner, M.A.2
  • 19
    • 0142000477 scopus 로고    scopus 로고
    • Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces
    • Storn R., and Price K. Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. J. Global Optim. 11 (1997) 341-359
    • (1997) J. Global Optim. , vol.11 , pp. 341-359
    • Storn, R.1    Price, K.2
  • 21
    • 33745603720 scopus 로고    scopus 로고
    • A Markov Chain Monte Carlo version of the genetic algorithm differential evolution: Easy Bayesian computing for real parameter spaces
    • Ter Braak C.J.F. A Markov Chain Monte Carlo version of the genetic algorithm differential evolution: Easy Bayesian computing for real parameter spaces. Statist. Comput. 16 (2006) 239-249
    • (2006) Statist. Comput. , vol.16 , pp. 239-249
    • Ter Braak, C.J.F.1
  • 22
    • 0031447220 scopus 로고    scopus 로고
    • Dynamic weighting in Monte Carlo and optimization
    • Wong W.H., and Liang F. Dynamic weighting in Monte Carlo and optimization. Proc. Natl. Acad. Sci. 94 (1997) 14220-14224
    • (1997) Proc. Natl. Acad. Sci. , vol.94 , pp. 14220-14224
    • Wong, W.H.1    Liang, F.2
  • 23
    • 6344293000 scopus 로고    scopus 로고
    • Standish, Abbass, and Bedau (Eds), MIT press
    • Yang S. In: Standish, Abbass, and Bedau (Eds). Adaptive Crossover in Genetic Algorithms Using Statistics Mechanism. Artificial Life vol. VIII (2002), MIT press 182-185
    • (2002) Artificial Life , vol.VIII , pp. 182-185
    • Yang, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.