A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood
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DOI: 10.1016/j.csda.2010.09.001
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- David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.
References listed on IDEAS
- David Ardia & Lennart Hoogerheide & Herman K. van Dijk, 2009. "To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods," Tinbergen Institute Discussion Papers 09-017/4, Tinbergen Institute.
- Geweke, John, 1989. "Bayesian Inference in Econometric Models Using Monte Carlo Integration," Econometrica, Econometric Society, vol. 57(6), pages 1317-1339, November.
- Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2009.
"Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i03).
- David Ardia & Lennart F. Hoogerheide & Herman K. van Dijk, 2008. "Adaptive Mixture of Student-t distributions as a Flexible Candidate Distribution for Efficient Simulation: the R Package AdMit," Tinbergen Institute Discussion Papers 08-062/4, Tinbergen Institute, revised 15 Dec 2008.
- Hoogerheide, Lennart F. & Kaashoek, Johan F. & van Dijk, Herman K., 2007.
"On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks,"
Journal of Econometrics, Elsevier, vol. 139(1), pages 154-180, July.
- HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & VAN DIJK, Herman K., 2005. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: An application of flexible sampling methods using neural networks," LIDAM Discussion Papers CORE 2005029, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- HOOGERHEIDE, Lennart F. & KAASHOEK, Johan F. & van DIJK, Herman K., 2007. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," LIDAM Reprints CORE 1922, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Hoogerheide, L.F. & Kaashoek, J.F. & van Dijk, H.K., 2005. "On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural networks," Econometric Institute Research Papers EI 2005-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Han C. & Carlin B. P., 2001. "Markov Chain Monte Carlo Methods for Computing Bayes Factors: A Comparative Review," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1122-1132, September.
- Kloek, Tuen & van Dijk, Herman K, 1978.
"Bayesian Estimates of Equation System Parameters: An Application of Integration by Monte Carlo,"
Econometrica, Econometric Society, vol. 46(1), pages 1-19, January.
- Kloek, T. & van Dijk, H. K., 1976. "BAYESIAN ESTIMATES OF EQUATION SYSTEM PARAMETERS An Application of Integration by Monte Carlo," Econometric Institute Archives 272139, Erasmus University Rotterdam.
- Ausin, Maria Concepcion & Galeano, Pedro, 2007.
"Bayesian estimation of the Gaussian mixture GARCH model,"
Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2636-2652, February.
- Galeano, Pedro, 2005. "Bayesian estimation of the gaussian mixture garch model," DES - Working Papers. Statistics and Econometrics. WS ws053605, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Hop, J Peter & Van Dijk, Herman K, 1992. "SISAM and MIXIN: Two Algorithms for the Computation of Posterior Moments and Densities Using Monte Carlo Integration," Computer Science in Economics & Management, Kluwer;Society for Computational Economics, vol. 5(3), pages 183-220, August.
- Bauwens, Luc & Bos, Charles S. & van Dijk, Herman K. & van Oest, Rutger D., 2004.
"Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods,"
Journal of Econometrics, Elsevier, vol. 123(2), pages 201-225, December.
- Bauwens, L. & Bos, C.S. & van Dijk, H.K. & van Oest, R.D., 2003. "Adaptive radial-based direction sampling; Some flexible and robust Monte Carlo integration methods," Econometric Institute Research Papers EI 2003-22, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- BAUWENS, Luc & BOS, Charles S. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2004. "Adaptive radial-based direction sampling: some flexible and robust Monte Carlo integration methods," LIDAM Reprints CORE 1731, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- John Geweke, 1999.
"Using simulation methods for bayesian econometric models: inference, development,and communication,"
Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 1-73.
- John Geweke, 1998. "Using simulation methods for Bayesian econometric models: inference, development, and communication," Staff Report 249, Federal Reserve Bank of Minneapolis.
- Fruhwirth-Schnatter S., 2001. "Markov Chain Monte Carlo Estimation of Classical and Dynamic Switching and Mixture Models," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 194-209, March.
- Jana Eklund & Sune Karlsson, 2007.
"Forecast Combination and Model Averaging Using Predictive Measures,"
Econometric Reviews, Taylor & Francis Journals, vol. 26(2-4), pages 329-363.
- Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging using Predictive Measures," Working Paper Series 191, Sveriges Riksbank (Central Bank of Sweden).
- Eklund, Jana & Karlsson, Sune, 2005. "Forecast Combination and Model Averaging Using Predictive Measures," CEPR Discussion Papers 5268, C.E.P.R. Discussion Papers.
- Ardia, David & Baştürk, Nalan & Hoogerheide, Lennart & van Dijk, Herman K., 2012.
"A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood,"
Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3398-3414.
- David Ardia & Nalan Basturk & Lennart Hoogerheide & Herman K. van Dijk, 2010. "A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihood," Tinbergen Institute Discussion Papers 10-059/4, Tinbergen Institute.
- Chib S. & Jeliazkov I., 2001. "Marginal Likelihood From the Metropolis-Hastings Output," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 270-281, March.
- van Dijk, H. K. & Kloek, T., 1980.
"Further experience in Bayesian analysis using Monte Carlo integration,"
Journal of Econometrics, Elsevier, vol. 14(3), pages 307-328, December.
- van Dijk, H. K. & Kloek, T., 1980. "Further Experience In Bayesian Analysis Using Monte Carlo Integration," Econometric Institute Archives 272261, Erasmus University Rotterdam.
- H. K. Van Dijk, 1999. "Some remarks on the simulation revolution in bayesian econometric inference," Econometric Reviews, Taylor & Francis Journals, vol. 18(1), pages 105-112.
- Newey, Whitney & West, Kenneth, 2014.
"A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix,"
Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
- Newey, Whitney K & West, Kenneth D, 1987. "A Simple, Positive Semi-definite, Heteroskedasticity and Autocorrelation Consistent Covariance Matrix," Econometrica, Econometric Society, vol. 55(3), pages 703-708, May.
- Whitney K. Newey & Kenneth D. West, 1986. "A Simple, Positive Semi-Definite, Heteroskedasticity and AutocorrelationConsistent Covariance Matrix," NBER Technical Working Papers 0055, National Bureau of Economic Research, Inc.
- John Geweke, 1999. "Using Simulation Methods for Bayesian Econometric Models," Computing in Economics and Finance 1999 832, Society for Computational Economics.
- Frühwirth-Schnatter, Sylvia & Wagner, Helga, 2008. "Marginal likelihoods for non-Gaussian models using auxiliary mixture sampling," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4608-4624, June.
- David, D. & Hoogerheide, L.F. & van Dijk, H.K., 2008. "The AdMit Package," Econometric Institute Research Papers EI 2008-17, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- Tatiana Miazhynskaia & Georg Dorffner, 2006. "A comparison of Bayesian model selection based on MCMC with an application to GARCH-type models," Statistical Papers, Springer, vol. 47(4), pages 525-549, October.
- Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2009.
"Adaptive Mixture of Student-t Distributions as a Flexible Candidate Distribution for Efficient Simulation: The R Package AdMit,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 29(i03).
- David Ardia & Lennart F. Hoogerheide & Herman K. van Dijk, 2008. "Adaptive Mixture of Student-t distributions as a Flexible Candidate Distribution for Efficient Simulation: the R Package AdMit," Tinbergen Institute Discussion Papers 08-062/4, Tinbergen Institute, revised 15 Dec 2008.
- Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2008. "Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: the R package AdMit," DQE Working Papers 9, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 07 Jan 2009.
- Ardia, David & Hoogerheide, Lennart F. & van Dijk, Herman K., 2008. "AdMit: Adaptive Mixtures of Student-t Distributions," DQE Working Papers 10, Department of Quantitative Economics, University of Freiburg/Fribourg Switzerland, revised 07 Jan 2009.
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More about this item
Keywords
Marginal likelihood; Bayes factor; Importance sampling; Bridge sampling; Adaptive mixture of Student-t distributions;All these keywords.
JEL classification:
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
Statistics
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