Dellaportas, P;
Tsionas, MG;
(2019)
Importance sampling from posterior distributions using copula-base approximations.
Journal of Econometrics
, 210
(1)
pp. 45-57.
10.1016/j.jeconom.2018.11.004.
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Abstract
We provide generic approximations to k-dimensional posterior distributions through an importance sampling strategy. The importance function is a product of k univariate of Student-t densities and a k-dimensional betaLiouville density. The parameters of the densities and the number of components in the mixtures are adaptively optimized along the Monte Carlo sampling. For challenging high dimensional latent Gaussian models we propose a nested importance function approximation. We apply the techniques to a range of econometric models that have appeared in the literature, and we document their satisfactory performance relative to the alternatives.
| Type: | Article |
|---|---|
| Title: | Importance sampling from posterior distributions using copula-base approximations |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.jeconom.2018.11.004 |
| Publisher version: | https://doi.org/10.1016/j.jeconom.2018.11.004 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/1571024 |
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