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Volumn 14, Issue 3, 2014, Pages 623-661

Adaptive Markov chain Monte Carlo sampling and estimation in Mata

Author keywords

Amcmc(); Amcmc_*(); Bayesian estimation; Bayesmixedlogit; Drawing from distributions; Markov chain Monte Carlo; Mata; Mcmccqreg; Mixed logit; St0354

Indexed keywords


EID: 85001114538     PISSN: 1536867X     EISSN: 15368734     Source Type: Journal    
DOI: 10.1177/1536867x1401400309     Document Type: Article
Times cited : (25)

References (12)
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  • 6
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    • Inference from simulations and monitoring convergence
    • S. Brooks, A. Gelman, G. L. Jones, and X.-L. Meng, Boca Raton, FL: Chapman & Hall/CRC
    • Gelman, A., and K. Shirley. 2011. Inference from simulations and monitoring convergence. In Handbook of Markov Chain Monte Carlo, ed. S. Brooks, A. Gelman, G. L. Jones, and X.-L. Meng, 163–174. Boca Raton, FL: Chapman & Hall/CRC.
    • (2011) Handbook of Markov Chain Monte Carlo , pp. 163-174
    • Gelman, A.1    Shirley, K.2
  • 7
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    • Introduction to Markov Chain Monte Carlo
    • S. Brooks, A. Gelman, G. L. Jones, and X.-L. Meng, Boca Raton, FL: Chapman & Hall/CRC
    • Geyer, C. J. 2011. Introduction to Markov Chain Monte Carlo. In Handbook of Markov Chain Monte Carlo, ed. S. Brooks, A. Gelman, G. L. Jones, and X.-L. Meng, 3–48. Boca Raton, FL: Chapman & Hall/CRC.
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  • 8
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    • Fitting mixed logit models by using maximum simulated likelihood
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    • Hole, A.R.1
  • 9
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    • Least absolute deviations estimation for the censored regression model
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  • 10
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    • Censored regression quantiles
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  • 11
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    • Optimal proposal distributions and adaptive MCMC
    • S. Brooks, A. Gelman, G. L. Jones, and X.-L. Meng, Boca Raton, FL: Chapman & Hall/CRC
    • Rosenthal, J. S. 2011. Optimal proposal distributions and adaptive MCMC. In Handbook of Markov Chain Monte Carlo, ed. S. Brooks, A. Gelman, G. L. Jones, and X.-L. Meng, 93–112. Boca Raton, FL: Chapman & Hall/CRC.
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    • Rosenthal, J.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.