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Volumn 46, Issue 4, 2009, Pages 938-959

Does waste recycling really improve the multi-proposal metropolis-hastings algorithm? An analysis based on control variates

Author keywords

Central limit theorem; Control variates; Ergodic theorem; Metropolis Hastings algorithm; Monte carlo markov chain; Multi proposal algorithm; Variance reduction

Indexed keywords


EID: 76449089530     PISSN: 00219002     EISSN: None     Source Type: Journal    
DOI: 10.1239/jap/1261670681     Document Type: Article
Times cited : (33)

References (13)
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  • 3
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  • 4
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    • Monte Carlo simulation of a many fermion study
    • CEPERLEY, D., CHESTER, G. V. AND KALOS, M. H. (1977). Monte Carlo simulation of a many fermion study. Phys. Rev. B 16, 3081-3099.
    • (1977) Phys. Rev. B , vol.16 , pp. 3081-3099
    • CEPERLEY, D.1    CHESTER, G.V.2    KALOS, M.H.3
  • 6
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    • Available at
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    • FRENKEL, D.1
  • 9
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    • Waste-recycling Monte Carlo
    • Computer Simulations in Condensed Matter: From Materials to Chemical Biology, Springer, Berlin, pp
    • FRENKEL, D. (2006). Waste-recycling Monte Carlo. In Computer Simulations in Condensed Matter: From Materials to Chemical Biology (Lecture Notes Phys. 703), Springer, Berlin, pp. 127-137.
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    • FRENKEL, D.1
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    • Geometric variance reduction in Markov chains: Application to value function and gradient estimation
    • MUNOS, R. (2006). Geometric variance reduction in Markov chains: application to value function and gradient estimation. J. Mach. Learn. Res. 7, 413-427.
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  • 12
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    • Optimum Monte-Carlo sampling using Markov chains
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.