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Volumn 7, Issue 1, 1998, Pages 1-22

Toward black-box sampling: A random-direction interior-point markov chain approach

Author keywords

Bayesian computation; Gibbs sampler; Hit and Run; Metropolis Hastings algorithm; Monte Carlo; Multidimensional integrals; Posterior distributions; Prior distributions; Simulation

Indexed keywords


EID: 0032221061     PISSN: 10618600     EISSN: 15372715     Source Type: Journal    
DOI: 10.1080/10618600.1998.10474758     Document Type: Article
Times cited : (15)

References (36)
  • 2
  • 3
    • 0010107912 scopus 로고
    • The Present and Future of Bayesian Multivariate Analysis
    • C.R. Rao, Amsterdam: North-Holland
    • Berger, J.O. (1993), “The Present and Future of Bayesian Multivariate Analysis,” in Multivariate Analysis: Future Directions, ed. C.R. Rao, Amsterdam: North-Holland, pp. 25-53.
    • (1993) Multivariate Analysis: Future Directions , pp. 25-53
    • Berger, J.O.1
  • 4
    • 0010104953 scopus 로고
    • Determining Retirement Patterns: Prediction for a Multinomial Distribution with Constrained Parameter Space
    • Berger, J.O., and Chen M.-H. (1993), “Determining Retirement Patterns: Prediction for a Multinomial Distribution with Constrained Parameter Space,” The Statistician, 42, 427-443.
    • (1993) The Statistician , vol.42 , pp. 427-443
    • Berger, J.O.1    Chen, M.-H.2
  • 5
    • 21844506388 scopus 로고
    • Importance Weighted Marginal Bayesian Posterior Density Estimation
    • Chen, M.-H. (1994), “Importance Weighted Marginal Bayesian Posterior Density Estimation,” Journal of the American Statistical Association, 89, 818-824.
    • (1994) Journal of the American Statistical Association , vol.89 , pp. 818-824
    • Chen, M.-H.1
  • 8
    • 0010209090 scopus 로고
    • Random-Direction Interior-Point Markov Chains: A Family of Black-Box Samplers
    • Alexandria, VA: American Statistical Association
    • Chen, M.-H., and Schmeiser, B.W (1994), “Random-Direction Interior-Point Markov Chains: A Family of Black-Box Samplers,” in Proceedings of the Section on Bayesian Statistical Science, Alexandria, VA: American Statistical Association, pp. 1-6.
    • (1994) Proceedings of the Section on Bayesian Statistical Science , pp. 1-6
    • Chen, M.-H.1    Schmeiser, B.W.2
  • 9
    • 0030260521 scopus 로고    scopus 로고
    • General Hit-and-Run Monte Carlo Sampling for Evaluating Multidimensional Integrals
    • Chen, M.-H., and Schmeiser, B.W (1996), “General Hit-and-Run Monte Carlo Sampling for Evaluating Multidimensional Integrals,” Operations Research Letters, 19, 161-169.
    • (1996) Operations Research Letters , vol.19 , pp. 161-169
    • Chen, M.-H.1    Schmeiser, B.W.2
  • 10
    • 21344474305 scopus 로고    scopus 로고
    • Accelerating Monte Carlo Markov Chain Convergence for Cumulative-link Generalized Linear Models
    • Cowles, M.K. (1996), “Accelerating Monte Carlo Markov Chain Convergence for Cumulative-link Generalized Linear Models,” Statistics and Computing, 6, 101-111.
    • (1996) Statistics and Computing , vol.6 , pp. 101-111
    • Cowles, M.K.1
  • 11
    • 0030539336 scopus 로고    scopus 로고
    • Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review
    • Cowles, M.K., and Carlin, B.P. (1996), “Markov Chain Monte Carlo Convergence Diagnostics: A Comparative Review,” Journal of the American Statistical Association, 91, 883-904.
    • (1996) Journal of the American Statistical Association , vol.91 , pp. 883-904
    • Cowles, M.K.1    Carlin, B.P.2
  • 13
    • 84950453504 scopus 로고
    • Bayesian Analysis of Constrained Parameter and Truncated Data Problems Using Gibbs Sampling
    • Gelfand, A.E., Smith, A.F.M., and Lee, T.M. (1992), “Bayesian Analysis of Constrained Parameter and Truncated Data Problems Using Gibbs Sampling,” Journal of American Statistical Association, 87, 523-532.
    • (1992) Journal of American Statistical Association , vol.87 , pp. 523-532
    • Gelfand, A.E.1    Smith, A.F.M.2    Lee, T.M.3
  • 14
    • 84972492387 scopus 로고
    • Inference from Iterative Simulation Using Multiple Sequences
    • Gelman A., and Rubin, D.B. (1992), “Inference from Iterative Simulation Using Multiple Sequences,” Statistical Science, 7, 457-511.
    • (1992) Statistical Science , vol.7 , pp. 457-511
    • Gelman, A.1    Rubin, D.B.2
  • 16
    • 0001667705 scopus 로고
    • Bayesian Inference in Econometrics Models Using Monte Carlo Integration
    • Geweke, J. (1989), “Bayesian Inference in Econometrics Models Using Monte Carlo Integration,” Economet-rica, 57, 1317-1340.
    • (1989) Economet-Rica , vol.57 , pp. 1317-1340
    • Geweke, J.1
  • 17
    • 84972511893 scopus 로고
    • Practical Markov Chain Monte Carlo
    • Geyer, C.J. (1992), “Practical Markov Chain Monte Carlo,” Statistical Science, 7, 473-511.
    • (1992) Statistical Science , vol.7 , pp. 473-511
    • Geyer, C.J.1
  • 18
    • 0001422224 scopus 로고
    • Derivative-Free Adaptive Rejection Sampling for Gibbs Sampling
    • J.M. Bernardo, J.O. Berger, D.V. Lindley, and A.F.M. Smith, London: Oxford University Press
    • Gilks, W.R. (1992), “Derivative-Free Adaptive Rejection Sampling for Gibbs Sampling,” in Bayesian Statistics 4, eds. J.M. Bernardo, J.O. Berger, D.V. Lindley, and A.F.M. Smith, London: Oxford University Press, pp. 641-665.
    • (1992) Bayesian Statistics , vol.4 , pp. 641-665
    • Gilks, W.R.1
  • 19
    • 0001178202 scopus 로고
    • A Language and Program for Complex Bayesian Modeling
    • Gilks, W.R., Thomas, A., and Spiegelhalter, D.J. (1994), “A Language and Program for Complex Bayesian Modeling,” The Statistician, 43, 169-177.
    • (1994) The Statistician , vol.43 , pp. 169-177
    • Gilks, W.R.1    Thomas, A.2    Spiegelhalter, D.J.3
  • 20
    • 0010162930 scopus 로고
    • Software for Bayesian Analysis: Current Status and Additional Needs
    • J.M. Bernardo, M.H.DeGroot, D.V.Lindley, and A.F.M. Smith, London: Oxford University Press
    • Goel, P.K. (1988), “Software for Bayesian Analysis: Current Status and Additional Needs,” in Bayesian Statistics 3, eds. J.M. Bernardo, M.H.DeGroot, D.V.Lindley, and A.F.M. Smith, London: Oxford University Press, pp. 173-188.
    • (1988) Bayesian Statistics 3 , pp. 173-188
    • Goel, P.K.1
  • 21
    • 77956890234 scopus 로고
    • Monte Carlo Sampling Methods Using Markov Chains and Their Applications
    • Hastings, W.K. (1970), “Monte Carlo Sampling Methods Using Markov Chains and Their Applications,” Biometrika, 57, 97-109.
    • (1970) Biometrika , vol.57 , pp. 97-109
    • Hastings, W.K.1
  • 22
    • 0347615204 scopus 로고
    • Discussion on the Meeting on the Gibbs Sampling and Other Markov Chain Monte Carlo Methods
    • Ser. B
    • JRSSB (1993), Discussion on the Meeting on the Gibbs Sampling and Other Markov Chain Monte Carlo Methods, Journal of the Royal Statistical Society, Ser. B, 55, 53-102.
    • (1993) Journal of the Royal Statistical Society , vol.55 , pp. 53-102
  • 25
    • 0030514309 scopus 로고    scopus 로고
    • Reparameterizing the Generalized Linear Model to Accelerate Gibbs Sampler Convergence
    • Nandram, B., and Chen, M.-H. (1996), “Reparameterizing the Generalized Linear Model to Accelerate Gibbs Sampler Convergence,” Journal of Statistical Computation and Simulation, 54, 129-144.
    • (1996) Journal of Statistical Computation and Simulation , vol.54 , pp. 129-144
    • Nandram, B.1    Chen, M.-H.2
  • 27
    • 0000940729 scopus 로고
    • Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler
    • Ritter, C, and Tanner, M.A. (1992), “Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler,” Journal of the American Statistical Association, 87, 861-868.
    • (1992) Journal of the American Statistical Association , vol.87 , pp. 861-868
    • Ritter, C.1    Tanner, M.A.2
  • 30
    • 0021517318 scopus 로고
    • Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions
    • Smith, R. L. (1984), “Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed over Bounded Regions,” Operations Research, 32, 1297-1308.
    • (1984) Operations Research , vol.32 , pp. 1297-1308
    • Smith, R.L.1
  • 31
    • 0000605742 scopus 로고    scopus 로고
    • Computation on Bayesian Graphical Models
    • J.M. Bemado, J.O. Berger, A.P. Dawid, and A.F.M. Smith, London: Oxford University Press
    • Spiegelhalter, D.J., Thomas, A., and Best, N.G. (1996), “Computation on Bayesian Graphical Models,” in Bayesian Statistics 5, eds. J.M. Bemado, J.O. Berger, A.P. Dawid, and A.F.M. Smith, London: Oxford University Press, pp. 407-426.
    • (1996) Bayesian Statistics , vol.5 , pp. 407-426
    • Spiegelhalter, D.J.1    Thomas, A.2    Best, N.G.3
  • 33
  • 34
    • 0001279441 scopus 로고
    • BUGS: A Program to Perform Bayesian Inference Using Gibbs Sampling
    • J.M. Bernardo, J.O. Berger, D.V. Lindley, and A.F.M. Smith, London: Oxford University Press
    • Thomas, A., Spiegelhalter, D.J., and Gilks, W.R. (1992), “BUGS: A Program to Perform Bayesian Inference Using Gibbs Sampling,” in Bayesian Statistics 4, eds. J.M. Bernardo, J.O. Berger, D.V. Lindley, and A.F.M. Smith, London: Oxford University Press, pp. 837-842.
    • (1992) Bayesian Statistics , vol.4 , pp. 837-842
    • Thomas, A.1    Spiegelhalter, D.J.2    Gilks, W.R.3
  • 35
    • 0000576595 scopus 로고
    • Markov Chains for Exploring Posterior Distributions
    • (with discussion)
    • Tierney, L. (1994), “Markov Chains for Exploring Posterior Distributions” (with discussion), The Annals of Statistics, 22, 1701-1762.
    • (1994) The Annals of Statistics , vol.22 , pp. 1701-1762
    • Tierney, L.1
  • 36
    • 0010162081 scopus 로고
    • Monte Carlo Importance Sampling in Bayesian Statistics
    • N. Flournoy and R. Tsutakawa, Contemporary Mathematics
    • Wolpert, R.L. (1991), “Monte Carlo Importance Sampling in Bayesian Statistics,” in Statistical Multiple Integration, eds. N. Flournoy and R. Tsutakawa, Contemporary Mathematics, 116, 101-115.
    • (1991) Statistical Multiple Integration , vol.116 , pp. 101-115
    • Wolpert, R.L.1


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