This paper provides a construction of a Fleming-Viot measure valued diffusion process, for which the transition function is known, by extending recent ideas of Gibbs sampler based Markov processes. In particular, we concentrate on the Chapman-Kolmogorov consistency conditions which allows a...

We provide details on the full reconstruction of the dynamic equations from measured time series data, given the general class of the underlying physical process. Our results can be used by researchers in physical modelling and statistical mechanics interested in an efficient estimation of low...

This paper provides a construction of a Fleming-Viot measure valued diffusion process, for which the transition function is known, by extending recent ideas of Gibbs sampler based Markov processes. In particular, we concentrate on the Chapman-Kolmogorov consistency conditions which allows a...

A Bayesian nonparametric approach to modeling a nonlinear dynamic model is presented. New techniques for sampling infinite mixture models are used. The inference procedure specifically in the case of the logistic model and when the nonparametric component is applied to the additive errors is...

An approach to modeling dependent nonparametric random density functions is presented. This is based on the well known mixture of Dirichlet process model. The idea is to use a technique for constructing dependent random variables, first used for dependent gamma random variables. While the...