AdMit: Adaptive mixtures of Student-t distributions
David Ardia, Lennart Hoogerheide & Herman Van Dijk
| Résumé |
This short note presents the R package AdMit which provides flexible
functions to approximate a certain target distribution and it
provides an efficient sample of random draws from it, given only a
kernel of the target density function. The estimation procedure is
fully automatic and thus avoids the time-consuming and difficult
task of tuning a sampling algorithm. To illustrate the use of the
package, we apply the AdMit methodology to a bivariate bimodal
distribution. We describe the use of the functions provided by the
package and document the ability and relevance of the methodology
to reproduce the shape of non-elliptical distributions. |
| Mots-clés |
Adaptive mixture, Student-t distributions, importance sampling, independence chain Metropolis-Hasting algorithm, Bayesian, R software |
| Citation | Ardia, D., Hoogerheide, L., & Van Dijk , H. (2009). AdMit: Adaptive mixtures of Student-t distributions. The R Journal, 1(1), 25-30. |
| Type | Article de périodique (Anglais) |
| Date de publication | 2009 |
| Nom du périodique | The R Journal |
| Volume | 1 |
| Numéro | 1 |
| Pages | 25-30 |
| URL | https://journal.r-project.org/archive/2009-1/RJournal_200... |
| Liée au projet | Bayesian estimation of regime-switching GARCH models |