Journal of computational and graphical statisticsâ€¦

2010

We present a case-study on the utility of graphics cards to perform massively parallel simulation of advanced Monte Carlo methods. Graphics cards, containing multiple Graphics Processing Unitsâ€¦ (More)

In sequential decision problems in an unknown environment, the decision maker often faces a dilemma over whether to explore to discover more about the environment, or to exploit current knowledge. Weâ€¦ (More)

We introduce a general form of sequential Monte Carlo algorithm defined in terms of a parameterized resampling mechanism. We find that a suitably generalized notion of the Effective Sample Sizeâ€¦ (More)

We establish quantitative bounds for rates of convergence and asymptotic variances for iterated conditional sequential Monte Carlo (i-cSMC) Markov chains and associated particle Gibbs samplers [1].â€¦ (More)

In the following article we investigate a particle filter for approximating Feynman-Kac models with indicator potentials and we use this algorithm within Markov chain Monte Carlo (MCMC) to learnâ€¦ (More)

Proceedings Title: Proceedings of the 2012 Winterâ€¦

2012

Approximate Bayesian computation (ABC) is a class of simulation-based statistical inference procedures that are increasingly being applied in scenarios where the likelihood function is eitherâ€¦ (More)

This paper brings explicit considerations of distributed computing architectures and data structures into the rigorous design of Sequential Monte Carlo (SMC) methods. A theoretical result establishedâ€¦ (More)

p=1 ï£²ï£³I ( k p 6= k p, k pâˆ’1 = a k p pâˆ’1 ) + I ( k p = k 1 p ) Gpâˆ’1(z k pâˆ’1 pâˆ’1 ) âˆ‘Npâˆ’1 j=1 Gpâˆ’1(z j pâˆ’1) ï£½ï£¾ . Note that with a, z fixed C1(a, z; Â·) is a probability mass function on [N0:n], as isâ€¦ (More)