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Bayesian computational methods

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Authors : Robert, Christian P. (Author of the conference)
CIRM (Publisher )

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Abstract : This is a short introduction to the many directions of current research in Bayesian computational statistics, from accelerating MCMC algorithms, to using partly deterministic Markov processes like the bouncy particle and the zigzag samplers, to approximating the target or the proposal distributions in such methods. The main illustration focuses on the evaluation of normalising constants and ratios of normalising constants.

Keywords : Bayesian computation; Bayesian statistics; Markov chain Monte Carlo; MCMC simulation; computational methods

MSC Codes :
62C10 - Bayesian problems; characterization of Bayes procedures
62F15 - Bayesian inference
65C05 - Monte Carlo methods
65C60 - Computational problems in statistics

    Information on the Video

    Film maker : Hennenfent, Guillaume
    Language : English
    Available date : 12/11/2018
    Conference Date : 23/10/2018
    Subseries : Research School
    arXiv category : Computation ; Methodology
    Mathematical Area(s) : Probability & Statistics
    Format : MP4 (.mp4) - HD
    Video Time : 01:58:23
    Targeted Audience : Researchers ; Graduate Students
    Download : https://videos.cirm-math.fr/2018-10-23_Robert.mp4

Information on the Event

Event Title : Jean-Morlet chair: Masterclass in Bayesian statistics / Chaire Jean-Morlet : École de statistique bayésienne
Event Organizers : Chopin, Nicolas ; Mengersen, Kerrie ; Pommeret, Denys ; Pudlo, Pierre ; Robert, Christian P. ; Ryder, Robin
Dates : 22/10/2018 - 26/10/2018
Event Year : 2018
Event URL : https://www.chairejeanmorlet.com/1854.html

Citation Data

DOI : 10.24350/CIRM.V.19468303
Cite this video as: Robert, Christian P. (2018). Bayesian computational methods. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19468303
URI : http://dx.doi.org/10.24350/CIRM.V.19468303

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