Français
An introduction to particle filters
Multi angle
Authors : Chopin, Nicolas (Author of the conference)
CIRM (Publisher )
60J22 - Computational methods in Markov chains
62D05 - Sampling theory, sample surveys
62F15 - Bayesian inference
62M05 - Markov processes: estimation
62M20 - Prediction; filtering (statistics)
65C05 - Monte Carlo methods
CIRM (Publisher )
Loading the player...
|
Abstract :
This course will give a gentle introduction to SMC (Sequential Monte Carlo algorithms):
• motivation: state-space (hidden Markov) models, sequential analysis of such models; non-sequential problems that may be tackled using SMC.
• Formalism: Markov kernels, Feynman-Kac distributions.
• Monte Carlo tricks: importance sampling and resampling
• standard particle filters: bootstrap, guided, auxiliary
• maximum likelihood estimation of state-stace models
• Bayesian estimation of these models: PMCMC, SMC$^2$.
Keywords : sequential Monte Carlo methods; state-space model; resample-move algorithm; particle filtering; maximum likelihood estimators (MLE); Bayesian estimation
MSC Codes : • motivation: state-space (hidden Markov) models, sequential analysis of such models; non-sequential problems that may be tackled using SMC.
• Formalism: Markov kernels, Feynman-Kac distributions.
• Monte Carlo tricks: importance sampling and resampling
• standard particle filters: bootstrap, guided, auxiliary
• maximum likelihood estimation of state-stace models
• Bayesian estimation of these models: PMCMC, SMC$^2$.
Keywords : sequential Monte Carlo methods; state-space model; resample-move algorithm; particle filtering; maximum likelihood estimators (MLE); Bayesian estimation
60J22 - Computational methods in Markov chains
62D05 - Sampling theory, sample surveys
62F15 - Bayesian inference
62M05 - Markov processes: estimation
62M20 - Prediction; filtering (statistics)
65C05 - Monte Carlo methods
|
Information on the Video
Film maker : Hennenfent, GuillaumeLanguage : English Available date : 12/11/2018 Conference Date : 25/10/2018 Subseries : Research School arXiv category : Computation ; Statistics Mathematical Area(s) : Probability & Statistics Format : MP4 (.mp4) - HD Video Time : 01:59:38 Targeted Audience : Researchers ; Graduate Students Download : https://videos.cirm-math.fr/2018-10-25_Chopin.mp4 
|
Information on the Event
Event Title : Jean-Morlet chair: Masterclass in Bayesian statistics / Chaire Jean-Morlet : École de statistique bayésienneEvent 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.19468603Cite this video as: Chopin, Nicolas (2018). An introduction to particle filters. CIRM. Audiovisual resource. doi:10.24350/CIRM.V.19468603 URI : http://dx.doi.org/10.24350/CIRM.V.19468603 |
See Also
- [Multi angle] Model assessment, selection and averaging / Author of the conference Vehtari, Aki.
- [Multi angle] Bayesian computation with INLA / Author of the conference Rue, Havard.
- [Multi angle] Bayesian computational methods / Author of the conference Robert, Christian P..
- [Post-edited] Bayesian modelling / Author of the conference Mengersen, Kerrie.
Bibliography
