English
Markov Chain Monte Carlo Methods - Part 1
Post-edited
Auteurs : Robert, Christian P. (Auteur de la Conférence)
CIRM (Editeur )
60J10 - Markov chains (discrete-time Markov processes on discrete state spaces)
62F15 - Bayesian inference
65C05 - Monte Carlo methods
65C40 - Computational Markov chains (numerical analysis)
CIRM (Editeur )
Résumé :
In this short course, we recall the basics of Markov chain Monte Carlo (Gibbs & Metropolis sampelrs) along with the most recent developments like Hamiltonian Monte Carlo, Rao-Blackwellisation, divide & conquer strategies, pseudo-marginal and other noisy versions. We also cover the specific approximate method of ABC that is currently used in many fields to handle complex models in manageable conditions, from the original motivation in population genetics to the several reinterpretations of the approach found in the recent literature. Time allowing, we will also comment on the programming developments like BUGS, STAN and Anglican that stemmed from those specific algorithms.
Codes MSC : 60J10 - Markov chains (discrete-time Markov processes on discrete state spaces)
62F15 - Bayesian inference
65C05 - Monte Carlo methods
65C40 - Computational Markov chains (numerical analysis)
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Informations sur la Vidéo
Réalisateur : Hennenfent, GuillaumeLangue : Anglais Date de publication : 16/03/16 Date de captation : 29/02/16 Sous collection : Research talks arXiv category : Statistics Theory ; Computer Science Domaine : Probability & Statistics Format : MP4 (.mp4) - HD Durée : 01:05:32 Audience : Researchers Download : https://videos.cirm-math.fr/2016-02-29_Robert.mp4 
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Informations sur la Rencontre
Nom de la rencontre : Thematic month on statistics - Week 5: Bayesian statistics and algorithms / Mois thématique sur les statistiques - Semaine 5 : Semaine Bayésienne et algorithmesOrganisateurs de la rencontre : Le Gouic, Thibaut ; Pommeret, Denys ; Willer, Thomas Dates : 29/02/2016 - 04/03/16 Année de la rencontre : 2016 URL Congrès : http://conferences.cirm-math.fr/1619.html
Données de citation
DOI : 10.24350/CIRM.V.18936903Citer cette vidéo: Robert, Christian P. (2016). Markov Chain Monte Carlo Methods - Part 1. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.18936903 URI : http://dx.doi.org/10.24350/CIRM.V.18936903 |
Voir aussi
- [Multi angle] Variational Bayes methods and algorithms - Part 1 / Auteur de la Conférence Keribin, Christine.
- [Multi angle] The expectation-propagation algorithm: a tutorial - Part 1 / Auteur de la Conférence Barthelmé, Simon.
- [Multi angle] Exploring the presence of complex dependence structures in epidemiological and genomic data through flexible clustering / Auteur de la Conférence Richardson, Sylvia.
- [Multi angle] Approximate Bayesian Computation methods for model choice a machine learning point of view - Part 1 / Auteur de la Conférence Marin, Jean-Michel.
Bibliographie
- Robert, C.P., & Casella, G. (2010). Introducing Monte Carlo methods with R. New York : Springer - http://dx.doi.org/10.1007/978-1-4419-1576-4
- Robert, C.P., & Casella, G. (2004). Monte Carlo statistical methods. New York : Springer - http://dx.doi.org/10.1007/978-1-4757-4145-2
