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  4. AdMit: Adaptive mixtures of Student-t distributions
 
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AdMit: Adaptive mixtures of Student-t distributions

Auteur(s)
Ardia, David 
Institut d'analyse financière 
Hoogerheide, Lennart
Van Dijk, Herman
Date de parution
2009
In
The R Journal
Vol.
1
No
1
De la page
25
A la page
30
Revu par les pairs
1
Mots-clés
  • Adaptive mixture
  • Student-t distributions
  • importance sampling
  • independence chain Metropolis-Hasting algorithm
  • Bayesian
  • R software
  • Adaptive mixture

  • Student-t distributio...

  • importance sampling

  • independence chain Me...

  • Bayesian

  • R software

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.
Lié au projet
Bayesian estimation of regime-switching GARCH models 
Identifiants
https://libra.unine.ch/handle/123456789/24513
Autre version
https://journal.r-project.org/archive/2009-1/RJournal_2009-1_Ardia+et+al.pdf
Type de publication
journal article
Dossier(s) à télécharger
 main article: document.pdf (326.31 KB)
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