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Volumn 27, Issue 2, 2012, Pages 232-246

Joint specification of model space and parameter space prior distributions

Author keywords

Bayesian inference; BIC; Generalized linear models; Lindley's paradox; Model averaging; Regression models

Indexed keywords


EID: 84871583788     PISSN: 08834237     EISSN: None     Source Type: Journal    
DOI: 10.1214/11-STS369     Document Type: Article
Times cited : (22)

References (53)
  • 1
    • 0000609589 scopus 로고
    • Comment on D.V. Lindley's statistical paradox
    • BARTLETT, M. S. (1957). Comment on D. V. Lindley's statistical paradox. Biometrika 44 533-534.
    • (1957) Biometrika , vol.44 , pp. 533-534
    • Bartlett, M.S.1
  • 2
    • 0000298252 scopus 로고    scopus 로고
    • The intrinsic Bayes factor formodel selection and prediction
    • BERGER, J. O. and PERICCHI, L. R. (1996). The intrinsic Bayes factor formodel selection and prediction. J. Amer. Statist. Assoc. 91 109-122.
    • (1996) J. Amer. Statist. Assoc. , vol.91 , pp. 109-122
    • Berger, J.O.1    Pericchi, L.R.2
  • 3
    • 4043180931 scopus 로고    scopus 로고
    • Training samples in objective Bayesian model selection
    • BERGER, J. O. and PERICCHI, L. R. (2004). Training samples in objective Bayesian model selection. Ann. Statist. 32 841-869.
    • (2004) Ann. Statist. , vol.32 , pp. 841-869
    • Berger, J.O.1    Pericchi, L.R.2
  • 4
    • 0033474268 scopus 로고    scopus 로고
    • Prior elicitation, variable selection and Bayesian computation for logistic regression models
    • CHEN, M.-H., IBRAHIM, J. G. and YIANNOUTSOS, C. (1999). Prior elicitation, variable selection and Bayesian computation for logistic regression models. J. R. Stat. Soc. Ser. B Stat. Methodol. 61 223-242.
    • (1999) J. R. Stat. Soc. Ser. B Stat. Methodol. , vol.61 , pp. 223-242
    • Chen, M.-H.1    Ibrahim, J.G.2    Yiannoutsos, C.3
  • 5
    • 0037290198 scopus 로고    scopus 로고
    • Prior elicitation for model selection and estimation in generalized linear mixedmodels
    • CHEN, M.-H., IBRAHIM, J. G., SHAO, Q.-M. andWEISS, R. E. (2003). Prior elicitation for model selection and estimation in generalized linear mixedmodels. J. Statist. Plann. Inference 111 57-76.
    • (2003) J. Statist. Plann. Inference , vol.111 , pp. 57-76
    • Chen, M.-H.1    Ibrahim, J.G.2    Shao, Q.-M.3    Weiss, R.E.4
  • 6
    • 0030532505 scopus 로고    scopus 로고
    • Bayesian variable selection with related predictors
    • CHIPMAN, H. (1996). Bayesian variable selection with related predictors. Canad. J. Statist. 24 17-36.
    • (1996) Canad. J. Statist. , vol.24 , pp. 17-36
    • Chipman, H.1
  • 8
    • 0034541856 scopus 로고    scopus 로고
    • Model uncertainty and health effect studies for particulate matter
    • CLYDE, M. (2000). Model uncertainty and health effect studies for particulate matter. Environmetrics 11 745-763.
    • (2000) Environmetrics , vol.11 , pp. 745-763
    • Clyde, M.1
  • 10
    • 37249067120 scopus 로고    scopus 로고
    • Empirical Bayes vs. fully Bayes variable selection
    • CUI, W. and GEORGE, E. I. (2008). Empirical Bayes vs. fully Bayes variable selection. J. Statist. Plann. Inference 138 888-900.
    • (2008) J. Statist. Plann. Inference , vol.138 , pp. 888-900
    • Cui, W.1    George, E.I.2
  • 11
    • 84871586585 scopus 로고    scopus 로고
    • Posterior model probabilities
    • (P. S. Bandyopadhyay and M. Forster, eds.) Elsevier, New York
    • DAWID, A. P. (2011). Posterior model probabilities. In Philosophy of Statistics (P. S. Bandyopadhyay and M. Forster, eds.) 607-630. Elsevier, New York.
    • (2011) Philosophy of Statistics , pp. 607-630
    • Dawid, A.P.1
  • 12
    • 0000860415 scopus 로고    scopus 로고
    • Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models
    • DELLAPORTAS, P. and FORSTER, J. J. (1999). Markov chain Monte Carlo model determination for hierarchical and graphical log-linear models. Biometrika 86 615-633.
    • (1999) Biometrika , vol.86 , pp. 615-633
    • Dellaportas, P.1    Forster, J.J.2
  • 13
    • 0041696122 scopus 로고    scopus 로고
    • On Bayesian model and variable selection using MCMC
    • DELLAPORTAS, P., FORSTER, J. J. and NTZOUFRAS, I. (2002). On Bayesian model and variable selection using MCMC. Stat. Comput. 12 27-36.
    • (2002) Stat. Comput. , vol.12 , pp. 27-36
    • Dellaportas, P.1    Forster, J.J.2    Ntzoufras, I.3
  • 15
    • 18044404766 scopus 로고    scopus 로고
    • Benchmark priors for Bayesian model averaging
    • FERNÁNDEZ, C., LEY, E. and STEEL, M. F. J. (2001). Benchmark priors for Bayesian model averaging. J. Econometrics 100 381-427.
    • (2001) J. Econometrics , vol.100 , pp. 381-427
    • Fernández, C.1    Ley, E.2    Steel, M.F.J.3
  • 16
    • 21844523862 scopus 로고
    • The risk inflation criterion for multiple regression
    • FOSTER, D. P. and GEORGE, E. I. (1994). The risk inflation criterion for multiple regression. Ann. Statist. 22 1947-1975.
    • (1994) Ann. Statist. , vol.22 , pp. 1947-1975
    • Foster, D.P.1    George, E.I.2
  • 17
    • 0001526195 scopus 로고
    • A predictive approach to model selection
    • GEISSER, S. and EDDY, W. F. (1979). A predictive approach to model selection. J. Amer. Statist. Assoc. 74 153-160.
    • (1979) J. Amer. Statist. Assoc. , vol.74 , pp. 153-160
    • Geisser, S.1    Eddy, W.F.2
  • 18
    • 0001803816 scopus 로고    scopus 로고
    • Model determination using samplingbased methods
    • (W. R. Gilks, S. Richardson and D. J. Spiegelhalter, eds.) Chapman & Hall, London
    • GELFAND, A. E. (1996). Model determination using samplingbased methods. In Markov Chain Monte Carlo in Practice (W. R. Gilks, S. Richardson and D. J. Spiegelhalter, eds.) 145-161. Chapman & Hall, London.
    • (1996) Markov Chain Monte Carlo in Practice , pp. 145-161
    • Gelfand, A.E.1
  • 19
    • 0001729472 scopus 로고    scopus 로고
    • Calibration and empirical Bayes variable selection
    • GEORGE, E. I. and FOSTER, D. P. (2000). Calibration and empirical Bayes variable selection. Biometrika 87 731-747.
    • (2000) Biometrika , vol.87 , pp. 731-747
    • George, E.I.1    Foster, D.P.2
  • 21
    • 77956889087 scopus 로고
    • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    • GREEN, P. J. (1995). Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika 82 711-732.
    • (1995) Biometrika , vol.82 , pp. 711-732
    • Green, P.J.1
  • 22
    • 0346641850 scopus 로고    scopus 로고
    • Trans-dimensional Markov chain Monte Carlo
    • Oxford Statist. Sci. Ser. Oxford Univ. Press, Oxford
    • GREEN, P. J. (2003). Trans-dimensional Markov chain Monte Carlo. In Highly Structured Stochastic Systems. Oxford Statist. Sci. Ser. 27 179-206. Oxford Univ. Press, Oxford.
    • (2003) Highly Structured Stochastic Systems , vol.27 , pp. 179-206
    • Green, P.J.1
  • 23
    • 34250747348 scopus 로고    scopus 로고
    • Shotgun stochastic search for "large p" regression
    • HANS, C., DOBRA, A. andWEST, M. (2007). Shotgun stochastic search for "large p" regression. J. Amer. Statist. Assoc. 102 507-516.
    • (2007) J. Amer. Statist. Assoc. , vol.102 , pp. 507-516
    • Hans, C.1    Dobra, A.2    West, M.3
  • 26
    • 0001153759 scopus 로고
    • Asymptotic expansions associated with posterior distributions
    • JOHNSON, R. A. (1970). Asymptotic expansions associated with posterior distributions. Ann. Math. Statist. 41 851-864.
    • (1970) Ann. Math. Statist. , vol.41 , pp. 851-864
    • Johnson, R.A.1
  • 27
    • 2142781609 scopus 로고    scopus 로고
    • Methods and criteria for model selection
    • KADANE, J. B. and LAZAR, N. A. (2004). Methods and criteria for model selection. J. Amer. Statist. Assoc. 99 279-290.
    • (2004) J. Amer. Statist. Assoc. , vol.99 , pp. 279-290
    • Kadane, J.B.1    Lazar, N.A.2
  • 28
    • 0012983316 scopus 로고
    • Asymptotics in Bayesian computation
    • Bayesian Statistics, 3 (Valencia, 1987) Oxford Univ. Press, New York
    • KASS, R. E., TIERNEY, L. and KADANE, J. B. (1988). Asymptotics in Bayesian computation. In Bayesian Statistics, 3 (Valencia, 1987). Oxford Sci. Publ. 261-278. Oxford Univ. Press, New York.
    • (1988) Oxford Sci. Publ. , pp. 261-278
    • Kass, R.E.1    Tierney, L.2    Kadane, J.B.3
  • 29
    • 27944462549 scopus 로고
    • A reference Bayesian test for nested hypotheses and its relationship to the Schwarz criterion
    • KASS, R. E. andWASSERMAN, L. (1995). A reference Bayesian test for nested hypotheses and its relationship to the Schwarz criterion. J. Amer. Statist. Assoc. 90 928-934.
    • (1995) J. Amer. Statist. Assoc. , vol.90 , pp. 928-934
    • Kass, R.E.1    Wasserman, L.2
  • 30
    • 0024203638 scopus 로고
    • Incorporating prior information into the analysis of contingency tables
    • KNUIMAN, M. W. and SPEED, T. P. (1988). Incorporating prior information into the analysis of contingency tables. Biometrics 44 1061-1071.
    • (1988) Biometrics , vol.44 , pp. 1061-1071
    • Knuiman, M.W.1    Speed, T.P.2
  • 31
    • 0010081155 scopus 로고    scopus 로고
    • Nonparametric regression using linear combinations of basis functions
    • KOHN, R., SMITH, M. and CHAN, D. (2001). Nonparametric regression using linear combinations of basis functions. Stat. Comput. 11 313-322.
    • (2001) Stat. Comput. , vol.11 , pp. 313-322
    • Kohn, R.1    Smith, M.2    Chan, D.3
  • 33
    • 0010705129 scopus 로고    scopus 로고
    • Predictive specification of prior model probabilities in variable selection
    • LAUD, P. W. and IBRAHIM, J. G. (1996). Predictive specification of prior model probabilities in variable selection. Biometrika 83 267-274.
    • (1996) Biometrika , vol.83 , pp. 267-274
    • Laud, P.W.1    Ibrahim, J.G.2
  • 34
    • 67651246919 scopus 로고    scopus 로고
    • On the effect of prior assumptions in Bayesian model averaging with applications to growth regression
    • LEY, E. and STEEL, M. F. J. (2009). On the effect of prior assumptions in Bayesian model averaging with applications to growth regression. J. Appl. Econometrics 24 651-674.
    • (2009) J. Appl. Econometrics , vol.24 , pp. 651-674
    • Ley, E.1    Steel, M.F.J.2
  • 36
    • 0000810338 scopus 로고
    • A statistical paradox
    • LINDLEY, D. V. (1957). A statistical paradox. Biometrika 44 187-192.
    • (1957) Biometrika , vol.44 , pp. 187-192
    • Lindley, D.V.1
  • 39
    • 27944431773 scopus 로고    scopus 로고
    • Adaptive sampling for Bayesian variable selection
    • NOTT, D. J. and KOHN, R. (2005). Adaptive sampling for Bayesian variable selection. Biometrika 92 747-763.
    • (2005) Biometrika , vol.92 , pp. 747-763
    • Nott, D.J.1    Kohn, R.2
  • 40
    • 0037290161 scopus 로고    scopus 로고
    • Bayesian variable and link determination for generalised linear models
    • NTZOUFRAS, I., DELLAPORTAS, P. and FORSTER, J. J. (2003). Bayesian variable and link determination for generalised linear models. J. Statist. Plann. Inference 111 165-180.
    • (2003) J. Statist. Plann. Inference , vol.111 , pp. 165-180
    • Ntzoufras, I.1    Dellaportas, P.2    Forster, J.J.3
  • 41
    • 47749099376 scopus 로고    scopus 로고
    • Misinformation in the conjugate prior for the linear model with implications for free-knot spline modelling
    • (electronic)
    • PACIOREK, C. J. (2006). Misinformation in the conjugate prior for the linear model with implications for free-knot spline modelling. Bayesian Anal. 1 375-383 (electronic).
    • (2006) Bayesian Anal , vol.1 , pp. 375-383
    • Paciorek, C.J.1
  • 42
    • 23544470859 scopus 로고    scopus 로고
    • Expected-posterior prior distributions for model selection
    • PÉREZ, J. M. and BERGER, J. O. (2002). Expected-posterior prior distributions for model selection. Biometrika 89 491-511.
    • (2002) Biometrika , vol.89 , pp. 491-511
    • Pérez, J.M.1    Berger, J.O.2
  • 43
    • 0002204128 scopus 로고
    • An alternative to the standard Bayesian procedure for discrimination between normal linear models
    • PERICCHI, L. R. (1984). An alternative to the standard Bayesian procedure for discrimination between normal linear models. Biometrika 71 575-586.
    • (1984) Biometrika , vol.71 , pp. 575-586
    • Pericchi, L.R.1
  • 44
    • 0039176796 scopus 로고
    • On the posterior odds of time series models
    • POSKITT, D. S. and TREMAYNE, A. R. (1983). On the posterior odds of time series models. Biometrika 70 157-162.
    • (1983) Biometrika , vol.70 , pp. 157-162
    • Poskitt, D.S.1    Tremayne, A.R.2
  • 45
    • 0001201909 scopus 로고
    • Bayesian model selection for social research (with discussion)
    • (P. V. Marsden, ed.) Blackwell, Oxford
    • RAFTERY, A. E. (1995). Bayesian model selection for social research (with discussion). In Sociological Methodology 1995 (P. V. Marsden, ed.) 111-196. Blackwell, Oxford.
    • (1995) In Sociological Methodology 1995 , pp. 111-196
    • Raftery, A.E.1
  • 46
    • 0000297493 scopus 로고    scopus 로고
    • Approximate Bayes factors and accounting for model uncertainty in generalised linear models
    • RAFTERY, A. E. (1996). Approximate Bayes factors and accounting for model uncertainty in generalised linear models. Biometrika 83 251-266.
    • (1996) Biometrika , vol.83 , pp. 251-266
    • Raftery, A.E.1
  • 47
    • 0011890988 scopus 로고
    • A note on Jeffreys-Lindley paradox
    • ROBERT, C. P. (1993). A note on Jeffreys-Lindley paradox. Statist. Sinica 3 601-608.
    • (1993) Statist. Sinica , vol.3 , pp. 601-608
    • Robert, C.P.1
  • 49
    • 0000120766 scopus 로고
    • Estimating the dimension of a model
    • SCHWARZ, G. (1978). Estimating the dimension of a model. Ann. Statist. 6 461-464.
    • (1978) Ann. Statist. , vol.6 , pp. 461-464
    • Schwarz, G.1
  • 50
    • 0034059779 scopus 로고    scopus 로고
    • Bayesian information criterion for censored survival models
    • VOLINSKY, C. T. and RAFTERY, A. E. (2000). Bayesian information criterion for censored survival models. Biometrics 56 256-262.
    • (2000) Biometrics , vol.56 , pp. 256-262
    • Volinsky, C.T.1    Raftery, A.E.2
  • 52
    • 0002817906 scopus 로고
    • On assessing prior distributions and Bayesian regression analysis with g-prior distributions
    • Bayesian Econometrics Statist. North-Holland, Amsterdam
    • ZELLNER, A. (1986). On assessing prior distributions and Bayesian regression analysis with g-prior distributions. In Bayesian Inference and Decision Techniques. Stud. Bayesian Econometrics Statist. 6 233-243. North-Holland, Amsterdam.
    • (1986) Bayesian Inference and Decision Techniques. Stud. , vol.6 , pp. 233-243
    • Zellner, A.1
  • 53
    • 0039026915 scopus 로고
    • Posterior odds ratios for selected regression hypotheses
    • (Spain) (J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith, eds.) 585-603. Valencia University Press, Valencia
    • ZELLNER, A. and SIOW, A. (1980). Posterior odds ratios for selected regression hypotheses. In Bayesian Statistics 1. Proceedings of the First International Meeting held in Valencia (Spain) (J. M. Bernardo, M. H. DeGroot, D. V. Lindley and A. F. M. Smith, eds.) 585-603. Valencia University Press, Valencia.
    • (1980) Bayesian Statistics 1. Proceedings of the First International Meeting held in Valencia
    • Zellner, A.1    Siow, A.2


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