14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper FrPP.1

Robert, Christian (Univ. Paris-Dauphine)

Bayesian Computational Tools

Scheduled for presentation during the Plenary Session "Plenary III" (FrPP), Friday, March 31, 2006, 09:00−10:00, Concert Hall

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 16, 2018

Keywords Bayesian Methods, Particle Filtering/Monte Carlo Methods


The toolbox available in Bayesian Statistics has increased considerably in the past decade and it has opened new avenues for Bayesian inference, the first and foremost being Bayesian model choice. The MCMC and particle filter technologies have hugely increased the potential for Bayesian applications, in particular in missing variable models, as illustrated in this short tutorial. We will also mention a new direction in this field, namely the development of adaptive algorithms that avoid a lengthy tuning to fit the problem at hand by automatically modifying the parameters of the algorithm.