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@article{HuJo09,
	Author = {Hu, J. and Johnson, V.E.},
	Date-Added = {2019-12-09 16:11:50 +0000},
	Date-Modified = {2019-12-09 16:13:05 +0000},
	Journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
	Number = {1},
	Pages = {143-158},
	Title = {Bayesian model selection using test statistics},
	Volume = {71},
	Year = {2009}}

@article{Heldetal15,
	Author = {Held, L. and Saban{\'e}s Bov{\'e}, D. and Gravestock, I},
	Date-Added = {2019-12-09 15:27:40 +0000},
	Date-Modified = {2019-12-09 15:29:28 +0000},
	Journal = {Statistical Science},
	Pages = {242-257},
	Title = {Approximate Bayesian model selection with the deviance statistic},
	Volume = {30},
	Year = {2015}}

@article{Jo05,
	Author = {Valen E. Johnson},
	Date-Added = {2019-12-09 15:25:33 +0000},
	Date-Modified = {2019-12-09 15:26:40 +0000},
	Journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
	Number = {5},
	Pages = {689-701},
	Title = {Bayes factors based on test statistics},
	Volume = {67},
	Year = {2005}}

@techreport{Casetal19,
	Author = {Castellanos, Maria E. and Garcia-Donato, Gonzalo and Cabras, Stefano},
	Date-Added = {2019-07-30 07:53:49 +0000},
	Date-Modified = {2019-07-30 07:55:36 +0000},
	Institution = {Technical Report},
	Title = {A Model selection approach for Variable selection with cen- sored data},
	Year = {2019}}

@article{Jo08,
	Author = {Johnson, V.E.},
	Date-Added = {2019-02-01 11:46:39 +0000},
	Date-Modified = {2019-02-01 11:48:19 +0000},
	Journal = {Scandinavian Journal of Statistics},
	Number = {2},
	Pages = {354-368},
	Title = {Properties of {B}ayes factors based on test statistics},
	Volume = {35},
	Year = {2008}}

@article{Shaetal06,
	Author = {Sha, N. and Tadesse, M.G. and Vanucci, M.},
	Date-Added = {2019-02-01 11:33:58 +0000},
	Date-Modified = {2019-02-01 11:35:36 +0000},
	Journal = {Bioinformatics},
	Number = {18},
	Pages = {2262-2268},
	Title = {Bayesian variable selection for the analysis of microarray data with censored outcomes},
	Volume = {22},
	Year = {2006}}

@article{Consetal18,
	Author = {Consonni, G. and Fouskakis, D. and Liseo, B. and Ntzoufras, I.},
	Date-Added = {2019-01-31 09:05:33 +0000},
	Date-Modified = {2019-01-31 09:07:29 +0000},
	Journal = {Bayesian Analysis},
	Pages = {627-679},
	Title = {Prior distributions for objective Bayesian analysis},
	Volume = {13},
	Year = {2018}}

@article{2016-Held,
	Author = {Held, L. and Gravestocka, I. and Saban{\'e}s Bov{\'e}, D.},
	Date-Added = {2019-01-22 13:22:15 +0100},
	Date-Modified = {2019-12-11 15:33:50 +0000},
	Journal = {Statistics in medicine},
	Pages = {5376--5390},
	Title = {Objective Bayesian model selection for Cox regression},
	Volume = {35},
	Year = {2016}}

@techreport{2018-Nikooienejad,
	Author = {Nikooienejad, A. and Wang, W. and Johnson, V.E.},
	Date-Added = {2019-01-22 13:18:26 +0100},
	Date-Modified = {2019-12-11 15:42:22 +0000},
	Institution = {Cornell University},
	Number = {arXiv:1712.02964},
	Title = {Bayesian Variable Selection For Survival Data Using Inverse Moment Priors},
	Year = {2018}}

@article{1999-Ibrahim,
	Author = {Joseph G. Ibrahim and Ming-Hui Chen and Steven N. MacEachern},
	Date-Added = {2019-01-22 13:08:01 +0100},
	Date-Modified = {2019-01-22 13:09:45 +0100},
	Journal = {Canadian Journal of Statistics},
	Number = {4},
	Pages = {701--717},
	Title = {Bayesian variable selection for proportional hazards models},
	Volume = {27},
	Year = {1999}}

@article{2002-Fan,
	Author = {Fan, J. and Li, R.},
	Date-Added = {2019-01-22 12:56:26 +0100},
	Date-Modified = {2019-01-22 13:01:04 +0100},
	Journal = {Annals of Statistics},
	Number = {1},
	Pages = {74-99},
	Title = {Variable selection for Cox's proportional hazards model and frailty},
	Volume = {30},
	Year = {2002}}

@article{2007-Candes,
	Author = {Candes, E. and Tau, T.},
	Date-Added = {2019-01-22 12:48:18 +0100},
	Date-Modified = {2019-12-11 15:30:41 +0000},
	Journal = {The Annals of Statistics},
	Number = {6},
	Pages = {2313--2351},
	Title = {The Dantzig Selector: Statistical Estimation When p Is Much Larger than n},
	Volume = {35},
	Year = {2007}}

@article{2010-Antoniadis,
	Author = {Antoniadis, A. and Fryzlewicz, P. and Letu{\'e}, F.},
	Date-Added = {2019-01-22 12:36:47 +0100},
	Date-Modified = {2019-01-22 12:53:31 +0100},
	Journal = {Scandinavian Journal of Statistics},
	Keywords = {Cox Model; dantzig selector},
	Number = {4},
	Pages = {531-552},
	Title = {The Dantzig Selector in Cox's Proportional Hazards Model.},
	Volume = {37},
	Year = {2010}}

@article{2007-Zhang,
	Abstract = {We investigate the variable selection problem for Cox's proportional hazards model, and propose a unified model selection and estimation procedure with desired theoretical properties and computational convenience. The new method is based on a penalized log partial likelihood with the adaptively weighted L₁ penalty on regression coefficients, providing what we call the adaptive Lasso estimator. The method incorporates different penalties for different coefficients: unimportant variables receive larger penalties than important ones, so that important variables tend to be retained in the selection process, whereas unimportant variables are more likely to be dropped. Theoretical properties, such as consistency and rate of convergence of the estimator, are studied. We also show that, with proper choice of regularization parameters, the proposed estimator has the oracle properties. The convex optimization nature of the method leads to an efficient algorithm. Both simulated and real examples show that the method performs competitively.},
	Author = {Zhang, H.H. and Lu, W.},
	Date-Added = {2019-01-22 12:28:14 +0100},
	Date-Modified = {2019-12-11 15:51:23 +0000},
	Issn = {00063444},
	Journal = {Biometrika},
	Number = {3},
	Pages = {691--703},
	Publisher = {[Oxford University Press, Biometrika Trust]},
	Title = {Adaptive Lasso for Cox's Proportional Hazards Model},
	Url = {http://www.jstor.org/stable/20441405},
	Volume = {94},
	Year = {2007},
	Bdsk-Url-1 = {http://www.jstor.org/stable/20441405}}

@article{DeSantis2001,
	Author = {De Santis, F. and Mortera, J. and Nardi, A.},
	Date-Added = {2016-05-17 12:55:38 +0000},
	Date-Modified = {2019-12-10 15:44:25 +0000},
	Journal = {Journal of statistical planning and inference},
	Number = {2},
	Pages = {193--209},
	Publisher = {Elsevier},
	Title = {Jeffreys priors for survival models with censored data},
	Volume = {99},
	Year = {2001}}

@article{LeySteel2009,
	Author = {Ley, Eduardo and Steel, Mark FJ},
	Date-Added = {2015-09-15 10:29:41 +0000},
	Date-Modified = {2015-09-15 10:29:41 +0000},
	Journal = {Journal of applied econometrics},
	Number = {4},
	Pages = {651--674},
	Publisher = {Wiley Online Library},
	Title = {On the effect of prior assumptions in Bayesian model averaging with applications to growth regression},
	Volume = {24},
	Year = {2009}}

@article{Santis2001,
	Author = {De Santis, Fulvio and Mortera, Julia and Nardi, Alessandra},
	Date-Added = {2015-07-15 08:54:53 +0000},
	Date-Modified = {2015-07-15 08:57:27 +0000},
	Journal = {Journal of statistical planning and inference},
	Number = {2},
	Pages = {193--209},
	Publisher = {Elsevier},
	Title = {Jeffreys priors for survival models with censored data},
	Volume = {99},
	Year = {2001}}

@article{cabras2015new,
	Author = {Cabras, S. and Castellanos, M.E. and Perra, S.},
	Date-Added = {2015-06-29 10:03:48 +0000},
	Date-Modified = {2019-12-10 15:41:35 +0000},
	Journal = {Computational Statistics \& Data Analysis},
	Pages = {52--63},
	Publisher = {Elsevier},
	Title = {A new minimal training sample scheme for intrinsic Bayes factors in censored data},
	Volume = {81},
	Year = {2015}}

@article{cabras2014comparison,
	Author = {Cabras, S. and Castellanos, M.E. and Perra, S.},
	Date-Added = {2015-06-29 10:01:32 +0000},
	Date-Modified = {2019-12-10 15:41:10 +0000},
	Journal = {Statistics in medicine},
	Number = {26},
	Pages = {4637--4654},
	Publisher = {Wiley Online Library},
	Title = {Comparison of objective {B}ayes factors for variable selection in parametric regression models for survival analysis},
	Volume = {33},
	Year = {2014}}

@book{perra-cabras-castellanos,
	Author = {Perra, S. and Cabras, S. and Castellanos, M.E.},
	Date-Added = {2015-06-29 10:00:43 +0000},
	Date-Modified = {2019-12-11 15:43:14 +0000},
	Publisher = {LAP Lambert Academic Publishing},
	Title = {Objective Bayesian Variable Selection for Censored Data},
	Year = {2013}}

@article{Lee:2014aa,
	Abstract = {Abstract Over the past decade much statistical research has been carried out to develop models for correlated survival data; however, methods for model selection are still very limited. A stochastic search variable selection (SSVS) approach under the proportional hazards mixed-effects model (PHMM) is developed. The SSVS method has previously been applied to linear and generalized linear mixed models, and to the proportional hazards model with high dimensional data. Because the method has mainly been developed for hierarchical normal mixture distributions, it operates on the linear predictor under the Cox type models. The PHMM naturally incorporates the normal distribution via the random effects, which enables SSVS to efficiently search through the candidate variable space. The approach was evaluated through simulation, and applied to a multi-center lung cancer clinical trial data set, for which the variable selection problem was previously debated upon in the literature.},
	Author = {Lee, Kyeong Eun and Kim, Yongku and Xu, Ronghui},
	Date = {2014/7//},
	Date-Added = {2015-06-29 08:56:16 +0000},
	Date-Modified = {2015-06-29 08:56:16 +0000},
	Doi = {http://dx.doi.org/10.1016/j.csda.2014.02.009},
	Isbn = {0167-9473},
	Journal = {Computational Statistics \& Data Analysis},
	Keywords = {Correlated survival data; MCMC; Model selection; Multi-center clinical trial; Proportional hazards mixed-effects model; Stochastic search variable selection},
	Month = {7},
	Number = {0},
	Pages = {53--65},
	Title = {Bayesian variable selection under the proportional hazards mixed-effects model},
	Ty = {JOUR},
	Url = {http://www.sciencedirect.com/science/article/pii/S0167947314000498},
	Volume = {75},
	Year = {2014},
	Bdsk-Url-1 = {http://www.sciencedirect.com/science/article/pii/S0167947314000498},
	Bdsk-Url-2 = {http://dx.doi.org/10.1016/j.csda.2014.02.009}}

@article{wagner-duller-2012,
	Author = {Helga Wagner and Christine Duller},
	Date-Added = {2015-06-29 08:55:51 +0000},
	Date-Modified = {2015-06-29 08:55:51 +0000},
	Journal = {Computational Statistics and Data Analysis},
	Number = {1},
	Pages = {1256--1274},
	Title = {Bayesian model selection for logistic regression models with random intercept},
	Volume = {56},
	Year = {2012}}

@article{Nott:2010aa,
	Abstract = {A Bayesian approach to variable selection which is based on the expected Kullback{\^a}€``Leibler divergence between the full model and its projection onto a submodel has recently been suggested in the literature. For generalized linear models an extension of this idea is proposed by considering projections onto subspaces defined via some form of L 1 constraint on the parameter in the full model. This leads to Bayesian model selection approaches related to the lasso. In the posterior distribution of the projection there is positive probability that some components are exactly zero and the posterior distribution on the model space induced by the projection allows exploration of model uncertainty. Use of the approach in structured variable selection problems such as ANOVA models is also considered, where it is desired to incorporate main effects in the presence of interactions. Projections related to the non-negative garotte are able to respect the hierarchical constraints. A consistency result is given concerning the posterior distribution on the model induced by the projection, showing that for some projections related to the adaptive lasso and non-negative garotte the posterior distribution concentrates on the true model asymptotically.},
	Author = {Nott, David J. and Leng, Chenlei},
	Date = {2010/12/1/},
	Date-Added = {2015-06-29 08:55:01 +0000},
	Date-Modified = {2015-06-29 08:55:01 +0000},
	Day = {1},
	Doi = {http://dx.doi.org/10.1016/j.csda.2010.01.036},
	Isbn = {0167-9473},
	Journal = {Computational Statistics \& Data Analysis},
	Keywords = {Bayesian variable selection; Kullback{\^a}€``Leibler projection; Lasso; Non-negative garotte; Preconditioning},
	Month = {12},
	Number = {12},
	Pages = {3227--3241},
	Title = {Bayesian projection approaches to variable selection in generalized linear models},
	Ty = {JOUR},
	Url = {http://www.sciencedirect.com/science/article/pii/S016794731000054X},
	Volume = {54},
	Year = {2010},
	Bdsk-Url-1 = {http://www.sciencedirect.com/science/article/pii/S016794731000054X},
	Bdsk-Url-2 = {http://dx.doi.org/10.1016/j.csda.2010.01.036}}

@article{KassWasserman1995,
	Abstract = {To compute a Bayes factor for testing H0: ψ = ψ0 in the presence of a nuisance parameter β, priors under the null and alternative hypotheses must be chosen. As in Bayesian estimation, an important problem has been to define automatic, or "reference," methods for determining priors based only on the structure of the model. In this article we apply the heuristic device of taking the amount of information in the prior on ψ equal to the amount of information in a single observation. Then, after transforming β to be "null orthogonal" to ψ, we take the marginal priors on β to be equal under the null and alternative hypotheses. Doing so, and taking the prior on ψ to be Normal, we find that the log of the Bayes factor may be approximated by the Schwarz criterion with an error of order Op(n-1/2), rather than the usual error of order Op(1). This result suggests the Schwarz criterion should provide sensible approximate solutions to Bayesian testing problems, at least when the hypotheses are nested. When instead the prior on ψ is elliptically Cauchy, a constant correction term must be added to the Schwarz criterion; the result then becomes a multidimensional generalization of Jeffreys's method.},
	Author = {Kass, Robert E. and Wasserman, Larry},
	Copyright = {Copyright {\copyright} 1995 American Statistical Association},
	Date-Added = {2014-01-23 12:34:34 +0000},
	Date-Modified = {2014-01-23 12:37:39 +0000},
	Issn = {01621459},
	Journal = {Journal of the American Statistical Association},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Sep., 1995},
	Language = {English},
	Number = {431},
	Pages = {pp. 928-934},
	Publisher = {American Statistical Association},
	Title = {A Reference Bayesian Test for Nested Hypotheses and its Relationship to the Schwarz Criterion},
	Url = {http://www.jstor.org/stable/2291327},
	Volume = {90},
	Year = {1995},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2291327}}

@article{BergerPericchiVarshavsky1998,
	Abstract = {In Bayesian analysis with a "minimal" data set and common noninformative priors, the (formal) marginal density of the data is surprisingly often independent of the error distribution. This results in great simplifications in certain model selection methodologies; for instance, the Intrinsic Bayes Factor for models with this property reduces simply to the Bayes factor with respect to the noninformative priors. The basic result holds for comparison of models which are invariant with respect to the same group structure. Indeed the condition reduces to a condition on the distributions of the common maximal invariant. In these situations, the marginal density of a "minimal" data set is typically available in closed form, regardless of the error distribution. This provides very useful expressions for computation of Intrinsic Bayes Factors in more general settings. The conditions for the results to hold are explored in some detail for nonnormal linear models and various transformations thereof.},
	Author = {Berger, James O. and Pericchi, Luis R. and Varshavsky, Julia A.},
	Copyright = {Copyright {\copyright} 1998 Indian Statistical Institute},
	Date-Added = {2014-01-23 12:00:52 +0000},
	Date-Modified = {2014-01-23 12:01:19 +0000},
	Issn = {0581572X},
	Journal = {Sankhy{\=a}: The Indian Journal of Statistics, Series A (1961-2002)},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Oct., 1998},
	Jstor_Issuetitle = {Bayesian Analysis},
	Language = {English},
	Number = {3},
	Pages = {pp. 307-321},
	Publisher = {Springer on behalf of the Indian Statistical Institute},
	Title = {Bayes Factors and Marginal Distributions in Invariant Situations},
	Url = {http://www.jstor.org/stable/25051210},
	Volume = {60},
	Year = {1998},
	Bdsk-Url-1 = {http://www.jstor.org/stable/25051210}}

@article{Liangetal2008,
	Abstract = {Zellner's g prior remains a popular conventional prior for use in Bayesian variable selection, despite several undesirable consistency issues. In this article we study mixtures of g priors as an alternative to default g priors that resolve many of the problems with the original formulation while maintaining the computational tractability that has made the g prior so popular. We present theoretical properties of the mixture g priors and provide real and simulated examples to compare the mixture formulation with fixed g priors, empirical Bayes approaches, and other default procedures.},
	Author = {Liang, Feng and Paulo, Rui and Molina, German and Clyde, Merlise A. and Berger, Jim O.},
	Copyright = {Copyright {\copyright} 2008 American Statistical Association},
	Date-Added = {2014-01-23 11:59:05 +0000},
	Date-Modified = {2014-01-23 11:59:31 +0000},
	Issn = {01621459},
	Journal = {Journal of the American Statistical Association},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Mar., 2008},
	Language = {English},
	Number = {481},
	Pages = {pp. 410-423},
	Publisher = {American Statistical Association},
	Title = {Mixtures of g Priors for Bayesian Variable Selection},
	Url = {http://www.jstor.org/stable/27640050},
	Volume = {103},
	Year = {2008},
	Bdsk-Url-1 = {http://www.jstor.org/stable/27640050}}

@book{Eaton89,
	Author = {M.L.Eaton},
	Date-Added = {2014-01-23 11:54:05 +0000},
	Date-Modified = {2014-01-23 11:54:43 +0000},
	Publisher = {Institute of Mathematical Statistics},
	Title = {Group Invariance Applications in Statistics},
	Year = {1989}}

@book{Jeffreys61,
	Author = {H. Jeffreys},
	Date-Added = {2014-01-23 10:51:59 +0000},
	Date-Modified = {2014-01-23 10:52:49 +0000},
	Publisher = {Oxford Univ. Press},
	Title = {The Theory of Probability},
	Year = {1961}}

@book{thesis-silvia2013,
	Author = {S. Perra and S. Cabras and M.E. Castellanos},
	Date-Added = {2014-01-23 08:57:13 +0000},
	Date-Modified = {2014-01-23 09:05:17 +0000},
	Publisher = {Amazon},
	Title = {Objective Bayesian Variable Selection for Censored Data},
	Year = {2013}}

@article{a-multistate2012,
	Author = {Carmen Armero and Stefano Cabras and Maria Eugenia Castellanos and Silvia Perra and Alicia Quir{\'o}s and Mauro Javier Oruez{\'a}bal and Javier S{\'a}nchez-Rubio},
	Date-Added = {2012-05-25 09:42:24 +0000},
	Date-Modified = {2012-05-25 11:01:35 +0000},
	Journal = {Statistical Methods in Medical Research},
	Owner = {stefano},
	Timestamp = {2013.06.17},
	Title = {Bayesian analysis of a disability model for lung cancer survival},
	Volume = {DOI: 10.1177/0962280212452803},
	Year = {(2012)}}

@article{scottberger2010,
	Author = {Scott, J.G. and Berger, J.O.},
	Date-Modified = {2015-06-29 09:00:31 +0000},
	Journal = {The Annals of Statistics},
	Number = {5},
	Pages = {2587--2619},
	Title = {Bayes and Empirical-Bayes Multiplicity Adjustment in the Variable-Selection Problem},
	Volume = {38},
	Year = {2010}}

@article{barbieri-berger2004,
	Author = {Barbieri, M. M. and Berger, J. O.},
	Date-Added = {2012-01-30 13:44:09 +0100},
	Date-Modified = {2012-01-30 13:44:09 +0100},
	Journal = {The Annals of Statistics},
	Number = {3},
	Pages = {870-897},
	Title = {Optimal Predictive Model Selection},
	Volume = {32},
	Year = {2004}}

@article{Bayarri2012,
	__Markedentry = {[stefano:6]},
	Author = {Bayarri, MJ and Berger, JO and Forte, A and Garc{\'\i}a-Donato, G},
	Journal = {The Annals of Statistics},
	Number = {3},
	Owner = {stefano},
	Pages = {1550--1577},
	Publisher = {Institute of Mathematical Statistics},
	Timestamp = {2013.05.24},
	Title = {Criteria for Bayesian model choice with application to variable selection},
	Url = {http://projecteuclid.org/euclid.aos/1346850065},
	Volume = {40},
	Year = {2012},
	Bdsk-Url-1 = {http://projecteuclid.org/euclid.aos/1346850065}}

@article{BergerMortera95,
	Author = {J.O. Berger and J. Mortera},
	Date-Added = {2012-01-19 18:05:43 +0100},
	Date-Modified = {2012-01-19 18:07:55 +0100},
	Journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
	Pages = {130-131},
	Title = {Discussion on `Fractional Bayes factor for model comparison'},
	Volume = {57},
	Year = {1995}}

@incollection{Berger99,
	Author = {James O. Berger},
	Booktitle = {Encyclopedia of Statistical Sciences},
	Date-Added = {2012-01-18 12:52:30 +0100},
	Date-Modified = {2012-01-18 13:06:13 +0100},
	Editor = {S. Kotz and S. Read and D. Banks},
	Pages = {20-29},
	Publisher = {New York: Wiley},
	Title = {Bayes Factors},
	Volume = {3},
	Year = {1999}}

@incollection{berger-pericchi2001,
	Abstract = {The basics of the Bayesian approach to model selection are first presented,
	as well as the motivations for the Bayesian approach. We then review
	four methods of developing default Bayesian procedures that have
	undergone considerable recent development, the Conventional Prior
	approach, the Bayes Information Criterion, the Intrinsic Bayes Factor,
	and the Fractional Bayes Factor. As part of the review, these methods
	are illustrated on examples involving the normal linear model. The
	later part of the chapter focuses on comparison of the four approaches,
	and includes an extensive discussion of criteria for judging model
	selection procedures.},
	Author = {Berger, J.O. and Pericchi, L.R.},
	Booktitle = {Model Selection},
	Copyright = {Copyright {\copyright} 2001 Institute of Mathematical Statistics},
	Date-Added = {2012-01-18 13:10:11 +0100},
	Date-Modified = {2019-12-10 15:38:54 +0000},
	Editor = {P. Lahiri},
	Issn = {07492170},
	Journal = {Lecture Notes-Monograph Series},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {2001},
	Jstor_Issuetitle = {Model Selection},
	Language = {English},
	Pages = {pp. 135-207},
	Publisher = {Institute of Mathematical Statistics},
	Title = {Objective Bayesian Methods for Model Selection: Introduction and Comparison},
	Url = {http://www.jstor.org/stable/4356165},
	Volume = {38},
	Year = {2001},
	Bdsk-Url-1 = {http://www.jstor.org/stable/4356165}}

@article{berger-pericchi2004,
	Author = {Berger, J. O. and Pericchi, L. R.},
	Copyright = {Copyright � 2004 Institute of Mathematical Statistics},
	Date-Added = {2012-01-18 13:25:56 +0100},
	Date-Modified = {2012-01-18 13:25:56 +0100},
	Issn = {00905364},
	Journal = {The Annals of Statistics},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Jun., 2004},
	Language = {English},
	Number = {3},
	Pages = {pp. 841-869},
	Publisher = {Institute of Mathematical Statistics},
	Title = {Training Samples in Objective Bayesian Model Selection},
	Url = {http://www.jstor.org/stable/3448577},
	Volume = {32},
	Year = {2004},
	Bdsk-Url-1 = {http://www.jstor.org/stable/3448577}}

@article{berger-pericchi1998,
	Author = {Berger, J. O. and Pericchi, L. R.},
	Copyright = {Copyright � 1998 Indian Statistical Institute},
	Date-Added = {2012-01-30 17:17:55 +0100},
	Date-Modified = {2012-01-30 17:17:55 +0100},
	Issn = {05815738},
	Journal = {Sankhy?: The Indian Journal of Statistics, Series B},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Apr., 1998},
	Jstor_Issuetitle = {Bayesian Analysis},
	Language = {English},
	Number = {1},
	Pages = {pp. 1-18},
	Publisher = {Springer on behalf of the Indian Statistical Institute},
	Title = {Accurate and Stable Bayesian Model Selection: The Median Intrinsic Bayes Factor},
	Url = {http://www.jstor.org/stable/25053019},
	Volume = {60},
	Year = {1998},
	Bdsk-Url-1 = {http://www.jstor.org/stable/25053019}}

@article{berger-pericchi1996a,
	Author = {Berger, J. O. and Pericchi, L. R.},
	Copyright = {Copyright � 1996 American Statistical Association},
	Date-Added = {2012-01-18 13:24:03 +0100},
	Date-Modified = {2012-01-18 13:24:03 +0100},
	Issn = {01621459},
	Journal = {Journal of the American Statistical Association},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Mar., 1996},
	Language = {English},
	Number = {433},
	Pages = {pp. 109-122},
	Publisher = {American Statistical Association},
	Title = {The Intrinsic Bayes Factor for Model Selection and Prediction},
	Url = {http://www.jstor.org/stable/2291387},
	Volume = {91},
	Year = {1996},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2291387}}

@article{bertolino2000,
	Author = {Bertolino, F. and Racugno, W. and Moreno, E.},
	Copyright = {Copyright 2000 Royal Statistical Society},
	Date-Added = {2012-09-18 09:51:11 +0000},
	Date-Modified = {2012-09-18 09:51:11 +0000},
	Issn = {00390526},
	Journal = {Journal of the Royal Statistical Society. Series D (The Statistician)},
	Language = {English},
	Number = {4},
	Pages = {pp. 503-517},
	Publisher = {Blackwell Publishing for the Royal Statistical Society},
	Title = {Bayesian Model Selection Approach to Analysis of Variance under Heteroscedasticity},
	Volume = {49},
	Year = {2000}}

@article{chib-jeliazkov2001,
	Author = {Chib, S. and Jeliazkov, I.},
	Date-Added = {2012-01-27 13:05:59 +0100},
	Date-Modified = {2012-01-27 13:05:59 +0100},
	Eprint = {http://pubs.amstat.org/doi/pdf/10.1198/016214501750332848},
	Journal = {Journal of the American Statistical Association},
	Number = {453},
	Pages = {270-281},
	Title = {Marginal Likelihood From the Metropolis--Hastings Output},
	Url = {http://pubs.amstat.org/doi/abs/10.1198/016214501750332848},
	Volume = {96},
	Year = {2001},
	Bdsk-Url-1 = {http://pubs.amstat.org/doi/abs/10.1198/016214501750332848}}

@inproceedings{clyde1999,
	Author = {Clyde, M.},
	Booktitle = {Bayesian Statistics},
	Date-Added = {2012-01-30 15:35:41 +0100},
	Date-Modified = {2019-12-11 15:55:03 +0000},
	Editor = {J.M. Bernardo and J.O. Berger and A.P. Dawid and A.F.M. Smith},
	Pages = {157-185},
	Publisher = {Oxford University Press},
	Title = {Bayesian Model Averaging and Model Search Strategies},
	Volume = {6},
	Year = {1999}}

@article{desantis1997,
	Author = {De Santis, Fulvio and Spezzaferri, Fulvio},
	Doi = {10.2307/3315344},
	Issn = {1708-945X},
	Journal = {Canadian Journal of Statistics},
	Keywords = {Bayes factor, Bayesian inference, model comparison, partial Bayes factor, robustness.},
	Number = {4},
	Pages = {503--515},
	Publisher = {Wiley-Blackwell},
	Title = {Alternative Bayes factors for model selection},
	Url = {http://dx.doi.org/10.2307/3315344},
	Volume = {25},
	Year = {1997},
	Bdsk-Url-1 = {http://dx.doi.org/10.2307/3315344}}

@book{ghosh2006,
	Address = {New York, NY},
	Author = {Ghosh, J. K. and Delampady, M. and Samanta, T.},
	Publisher = {Springer},
	Series = {Springer texts in statistics},
	Title = {An introduction to Bayesian analysis: theory and methods},
	Year = {2006}}

@article{Gilks95,
	Author = {W.R. Gilks},
	Date-Added = {2012-01-30 12:29:54 +0100},
	Date-Modified = {2012-01-30 12:32:16 +0100},
	Journal = {J. Royal Statistical Siciety B},
	Number = {1},
	Pages = {99-138},
	Title = {Discussion on `Fractional Bayes factor for model comparison'},
	Volume = {57},
	Year = {1995}}

@article{Hoetingetal1999,
	Abstract = {Standard statistical practice ignores model uncertainty. Data analysts
	typically select a model from some class of models and then proceed
	as if the selected model had generated the data. This approach ignores
	the uncertainty in model selection, leading to over-confident inferences
	and decisions that are more risky than one thinks they are. Bayesian
	model averaging (BMA) provides a coherent mechanism for accounting
	for this model uncertainty. Several methods for implementing BMA
	have recently emerged. We discuss these methods and present a number
	of examples. In these examples, BMA provides improved out-of-sample
	predictive performance. We also provide a catalogue of currently
	available BMA software.},
	Author = {Hoeting, Jennifer A. and Madigan, David and Raftery, Adrian E. and Volinsky, Chris T.},
	Copyright = {Copyright {\copyright} 1999 Institute of Mathematical Statistics},
	Date-Added = {2012-01-30 15:41:12 +0100},
	Date-Modified = {2012-01-30 15:42:04 +0100},
	Issn = {08834237},
	Journal = {Statistical Science},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Nov., 1999},
	Language = {English},
	Number = {4},
	Pages = {pp. 382-401},
	Publisher = {Institute of Mathematical Statistics},
	Title = {Bayesian Model Averaging: A Tutorial},
	Url = {http://www.jstor.org/stable/2676803},
	Volume = {14},
	Year = {1999},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2676803}}

@article{kardaun1983,
	Author = {Kardaun, O},
	Date-Added = {2012-04-10 15:54:34 +0000},
	Date-Modified = {2012-04-10 15:55:57 +0000},
	Journal = {Statistical Nederlandica},
	Pages = {103-126},
	Title = {Statistical Analysis of Male Larynx-Cancer Patients - A Case Study},
	Volume = {37},
	Year = {1983}}

@article{kass-raftery1995,
	Author = {Kass, R.E. and Raftery, A.E.},
	Date-Added = {2012-01-18 12:48:39 +0100},
	Date-Modified = {2012-01-18 12:48:39 +0100},
	Journal = {Journal of the American Statistical Association},
	Pages = {773-795},
	Title = {Bayes Factors},
	Volume = {90},
	Year = {1995}}

@article{KimSun2000,
	Author = {Seong W. Kim and Dongchu Sun},
	Date-Added = {2012-01-30 17:05:36 +0100},
	Date-Modified = {2012-01-30 17:09:16 +0100},
	Doi = {10.1023/A:1009641709382},
	Journal = {Lifetime Data Analysis},
	Number = {3},
	Pages = {251--269},
	Title = {Intrinsic Priors for Model Selection Using an Encompassing Model with Applications to Censored Failure Time Data},
	Volume = {6},
	Year = {2000},
	Bdsk-Url-1 = {http://www.springerlink.com/content/q0rt02jj06qjv1k0/fulltext.pdf},
	Bdsk-Url-2 = {http://dx.doi.org/10.1023/A:1009641709382}}

@book{Klein:2003fk,
	Address = {New York},
	Annote = {LDR 01373cam 22003014a 4500 001 12824911 005 20080307104342.0 008
	020620s2003 nyua b 001 0 eng 906 $a7$bcbc$corignew$d1$eocip$f20$gy-gencatlg
	925 0 $aacquire$b2 shelf copies$xpolicy default 955 $apc17 2002-06-20
	to ASCD$ijc14 2002-06-21$djc02 2002-06-21 to technician$ejc03 2002-06-21
	to Dewey$aaa01 2002-06-21$aps16 2003-07-18 1 copy rec'd., to CIP
	ver.$fjc03 2003-07-23$gjc03 2003-07-23 to BCCD$aja15 2004-02-25 Copy
	2 to BCCD 010 $a 2002026667 020 $a038795399X (alk. paper) 040 $aDLC$cDLC$dDLC
	042 $apcc 050 00 $aR853.S7$bK535 2003 082 00 $a610/.7/27$221 100
	1 $aKlein, John P.,$d1950- 245 10 $aSurvival analysis :$btechniques
	for censored and truncated data /$cJohn P. Klein, Melvin L. Moeschberger.
	250 $a2nd ed. 260 $aNew York :$bSpringer,$cc2003. 300 $axv, 536 p.
	:$bill. ;$c24 cm. 440 0 $aStatistics for biology and health 504 $aIncludes
	bibliographical references (p. [515]-525) and indexes. 650 0 $aSurvival
	analysis (Biometry) 700 1 $aMoeschberger, Melvin L. 856 42 $3Publisher
	description$uhttp://www.loc.gov/catdir/enhancements/fy0815/2002026667-d.html
	856 41 $3Table of contents only$uhttp://www.loc.gov/catdir/enhancements/fy0815/2002026667-t.html
	
	},
	Author = {Klein, John P. and Moeschberger, Melvin L},
	Call-Number = {R853.S7},
	Date-Added = {2012-04-10 15:48:25 +0000},
	Date-Modified = {2012-04-10 15:48:25 +0000},
	Dewey-Call-Number = {610/.7/27},
	Edition = {2nd ed},
	Genre = {Survival analysis (Biometry)},
	Isbn = {038795399X (alk. paper)},
	Library-Id = {2002026667},
	Publisher = {Springer},
	Title = {Survival analysis: techniques for censored and truncated data},
	Url = {http://www.loc.gov/catdir/enhancements/fy0815/2002026667-d.html},
	Year = {2003},
	Bdsk-Url-1 = {http://www.loc.gov/catdir/enhancements/fy0815/2002026667-d.html}}

@article{LinghamSivaganesan1999,
	Author = {Rama T. Lingham and S. Sivaganesan},
	Date-Added = {2012-01-30 17:13:22 +0100},
	Date-Modified = {2012-01-30 17:13:49 +0100},
	Doi = {10.1016/S0378-3758(98)00181-5},
	Issn = {0378-3758},
	Journal = {Journal of Statistical Planning and Inference},
	Keywords = {Weibull process},
	Number = {2},
	Pages = {195 - 220},
	Title = {Intrinsic Bayes factor approach to a test for the power law process},
	Url = {http://www.sciencedirect.com/science/article/pii/S0378375898001815},
	Volume = {77},
	Year = {1999},
	Bdsk-Url-1 = {http://www.sciencedirect.com/science/article/pii/S0378375898001815},
	Bdsk-Url-2 = {http://dx.doi.org/10.1016/S0378-3758(98)00181-5}}

@article{moreno1997,
	Author = {Moreno, E.},
	Date-Added = {2012-01-19 18:05:28 +0100},
	Date-Modified = {2012-01-19 18:05:28 +0100},
	Journal = {IMS Lecture Notes},
	Pages = {257-270},
	Title = {Bayes Factors for Intrinsic and Fractional Priors in Nested Models: Bayesian Robustness},
	Volume = {31},
	Year = {1997}}

@article{Morenoetal1999,
	Author = {E. Moreno and Francesco Bertolino and Walter Racugno},
	Date-Added = {2012-01-30 17:08:59 +0100},
	Date-Modified = {2012-01-30 17:09:56 +0100},
	Doi = {10.1016/S0378-3758(99)00070-1},
	Issn = {0378-3758},
	Journal = {Journal of Statistical Planning and Inference},
	Keywords = {Intrinsic priors},
	Number = {2},
	Pages = {323 - 333},
	Title = {Default Bayesian analysis of the Behrens-Fisher problem},
	Url = {http://www.sciencedirect.com/science/article/pii/S0378375899000701},
	Volume = {81},
	Year = {1999},
	Bdsk-Url-1 = {http://www.sciencedirect.com/science/article/pii/S0378375899000701},
	Bdsk-Url-2 = {http://dx.doi.org/10.1016/S0378-3758(99)00070-1}}

@article{Morenoetal1998,
	Abstract = {Improper priors typically arise in default Bayesian estimation problems.
	In the Bayesian approach to model selection or hypothesis testing,
	the main tool is the Bayes factor. When improper priors for the parameters
	appearing in the models are used, the Bayes factor is not well defined.
	The intrinsic Bayes factor introduced by Berger and Pericchi is an
	interesting method for overcoming that difficulty. That method is
	of particular interest as a means for generating proper prior distributions
	(intrinsic priors) for model comparison from the improper priors
	typically used in estimation. The goal of this article is to develop
	a limiting procedure that provides a solid justification for the
	use of Bayes factor with intrinsic priors. The procedure is formalized
	and discussed for nested and nonnested models. Illustrations and
	comparisons with other approximations to Bayes factors, such as the
	Bayesian information criterion of Schwarz and the fractional Bayes
	factor of O'Hagan are provided.},
	Author = {Moreno, Elias and Bertolino, Francesco and Racugno, Walter},
	Copyright = {Copyright {\copyright} 1998 American Statistical Association},
	Date-Added = {2012-01-30 17:06:39 +0100},
	Date-Modified = {2012-01-30 17:06:59 +0100},
	Issn = {01621459},
	Journal = {Journal of the American Statistical Association},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Dec., 1998},
	Language = {English},
	Number = {444},
	Pages = {pp. 1451-1460},
	Publisher = {American Statistical Association},
	Title = {An Intrinsic Limiting Procedure for Model Selection and Hypotheses Testing},
	Url = {http://www.jstor.org/stable/2670059},
	Volume = {93},
	Year = {1998},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2670059}}

@article{MorenoGiron08,
	Author = {E. Moreno and F.J. Gir{\'o}n},
	Date-Added = {2012-01-19 18:20:07 +0100},
	Date-Modified = {2012-01-19 18:21:27 +0100},
	Journal = {Test},
	Pages = {472-492},
	Title = {Comparison of Bayesian objective procedures for variable selection in linear regression},
	Volume = {3},
	Year = {2008}}

@article{ohagan1995,
	Author = {O'Hagan, A.},
	Copyright = {Copyright � 1995 Royal Statistical Society},
	Date-Added = {2012-01-18 13:24:29 +0100},
	Date-Modified = {2012-01-18 13:24:29 +0100},
	Issn = {00359246},
	Journal = {Journal of the Royal Statistical Society. Series B (Methodological)},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {1995},
	Language = {English},
	Number = {1},
	Pages = {pp. 99-138},
	Publisher = {Blackwell Publishing for the Royal Statistical Society},
	Title = {Fractional Bayes Factors for Model Comparison},
	Url = {http://www.jstor.org/stable/2346088},
	Volume = {57},
	Year = {1995},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2346088}}

@phdthesis{Varshavsky95,
	Author = {J. Varshavsky},
	Date-Added = {2012-01-23 17:04:42 +0100},
	Date-Modified = {2012-01-23 17:06:03 +0100},
	School = {Purdue University},
	Title = {On the develpment of intrinsic Bayes factors},
	Year = {1995}}

@article{volinsky-raftery2000,
	Author = {Volinsky, C. T. and Raftery, A. E.},
	Copyright = {Copyright � 2000 International Biometric Society},
	Date-Added = {2012-05-29 12:57:29 +0200},
	Date-Modified = {2012-05-29 12:57:29 +0200},
	Issn = {0006341X},
	Journal = {Biometrics},
	Jstor_Articletype = {research-article},
	Jstor_Formatteddate = {Mar., 2000},
	Language = {English},
	Number = {1},
	Pages = {pp. 256-262},
	Publisher = {International Biometric Society},
	Title = {Bayesian Information Criterion for Censored Survival Models},
	Url = {http://www.jstor.org/stable/2677130},
	Volume = {56},
	Year = {2000},
	Bdsk-Url-1 = {http://www.jstor.org/stable/2677130}}

@techreport{Yang97,
	Author = {R. Yang and J.O. Berger},
	Date-Added = {2012-01-18 13:18:47 +0100},
	Date-Modified = {2012-01-18 13:20:21 +0100},
	Institution = {Duke University},
	Number = {ISDS Discussion Paper 97-42},
	Title = {A Catalogue of Noninformative Priors},
	Year = {1997}}

@inproceedings{zellner-siow1980,
	Affiliation = {University of Chicago Chicago USA},
	Author = {Zellner, A. and Siow, A.},
	Booktitle = {Bayesian Statistics 1 (Eds. J.M. Bernardo and J.O. Berger and A.P. Dawid and A.F.M. Smith)},
	Date-Added = {2012-01-24 11:12:39 +0100},
	Date-Modified = {2012-01-31 10:38:07 +0100},
	Issn = {0041-0241},
	Issue = {1},
	Keyword = {Business and Economics},
	Note = {10.1007/BF02888369},
	Pages = {585-603},
	Publisher = {Springer Berlin / Heidelberg},
	Title = {Posterior odds ratios for selected regression hypotheses},
	Url = {http://dx.doi.org/10.1007/BF02888369},
	Volume = {31},
	Year = {1980},
	Bdsk-Url-1 = {http://dx.doi.org/10.1007/BF02888369}}

@article{diccio-bridge1997,
	Author = {DiCiccio, T. and Kass, R. and Raftery, A. and Wasserman, L.},
	Journal = {Journal of American Statistical Association},
	Pages = {903-915},
	Title = {Computing Bayes factors by combining simulation and asymptotic approximations},
	Volume = {92},
	Year = {1997}}