Some remarks on the simulation revolution in bayesian econometric inference
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DOI: 10.1080/07474939908800432
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Cited by:
- Michiel D. de Pooter & René Segers & Herman K. van Dijk, 2006. "On the Practice of Bayesian Inference in Basic Economic Time Series Models using Gibbs Sampling," Tinbergen Institute Discussion Papers 06-076/4, Tinbergen Institute.
- van Dijk Herman K., 2024. "Challenges and Opportunities for Twenty First Century Bayesian Econometricians: A Personal View," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 28(2), pages 155-176, April.
- Hoogerheide, L.F. & van Dijk, H.K. & van Oest, R.D., 2007.
"Simulation based bayesian econometric inference: principles and some recent computational advances,"
Econometric Institute Research Papers
EI 2007-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
- HOOGERHEIDE, Lennart F. & VAN DIJK, Herman K. & VAN OEST, Rutger D., 2007. "Simulation based Bayesian econometric inference: principles and some recent computational advances," LIDAM Discussion Papers CORE 2007015, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- 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.
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