Feynman-Kac measures and Interacting Particle systems :
Selected studies on : Advanced Monte Carlo Algorithms
This webpage presents an overview of resources related to particle Monte Carlo algorithms, and their connexions with sequential Monte Carlo models, interacting Markov Chain Monte Carlo samplers.
Sequential Monte Carlo methodology.
Interacting Markov Chain Monte Carlo models.
Particle Markov chain Monte Carlo methods.
Gibbs cloner models, randomized Algorithms with Splitting
Sequentially Interacting Markov Chain Monte Carlo models
Mean field interacting particle models
These Monte Carlo methodologies are of course closely related one to another. This list
is clearly far from being exhaustive, and it is partially biased towards my work on stochastic particle models.
More references and links to this subject can be added on demand. We also recommend to consult the related webpages
The software BIIPS is a general software developed by the INRIA team ALEA
for bayesian inference with interacting particle systems, a.k.a. Sequential Monte Carlo methods.
A demonstration of the BiiPS software for estimating the stochastic volatility of financial data can be found in
Sequential Monte Carlo Samplers (Del Moral P., Doucet A., Jasra A)
Journal of the Royal Society of Statistics, Series B. vol. 68, No. 3, pp. 411-436 (2006).
Sequential Monte Carlo Samplers (Del Moral P., Doucet A., Jasra A)
Journal of the Royal Society of Statistics, Series B. vol. 68, No. 3, pp. 411-436 (2006).