The AdMit Package
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References listed on IDEAS
- Lennart Hoogerheide & Herman K. van Dijk, 2008. "Possibly Ill-behaved Posteriors in Econometric Models," Tinbergen Institute Discussion Papers 08-036/4, Tinbergen Institute, revised 18 Apr 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.
- 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.
- 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.
Citations
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Cited by:
- 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.
- 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 & 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.
- Ardia, David & Hoogerheide, Lennart F., 2010.
"Efficient Bayesian estimation and combination of GARCH-type models,"
MPRA Paper
22919, University Library of Munich, Germany.
- David Ardia & Lennart F. Hoogerheide, 2010. "Efficient Bayesian Estimation and Combination of GARCH-Type Models," Tinbergen Institute Discussion Papers 10-046/4, Tinbergen Institute.
- 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.
- repec:jss:jstsof:29:i03 is not 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.
- Hoogerheide, Lennart & van Dijk, Herman K., 2010.
"Bayesian forecasting of Value at Risk and Expected Shortfall using adaptive importance sampling,"
International Journal of Forecasting, Elsevier, vol. 26(2), pages 231-247, April.
- Lennart Hoogerheide & Herman K. van Dijk, 2008. "Bayesian Forecasting of Value at Risk and Expected Shortfall using Adaptive Importance Sampling," Tinbergen Institute Discussion Papers 08-092/4, Tinbergen Institute.
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Keywords
Bayesian; R software; adaptive mixture; importance sampling; independence chain Metropolis-Hasting algorithm; student-t distribution;All these keywords.
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