5 papers
Variational State and Parameter Estimation
Jarrad Courts, Johannes Hendriks, Adrian Wills +2
This paper considers the problem of computing Bayesian estimates of both states and model parameters for nonlinear state-space models. Generally, this problem does not have a tract…
A Variational Expectation-Maximisation Algorithm for Learning Jump Markov Linear Systems
Mark P. Balenzuela, Adrian G. Wills, Christopher Renton +1
Jump Markov linear systems (JMLS) are a useful class which can be used to model processes which exhibit random changes in behavior during operation. This paper presents a numerical…
A New Smoothing Algorithm for Jump Markov Linear Systems
Mark P. Balenzuela, Adrian G. Wills, Christopher Renton +1
This paper presents a method for calculating the smoothed state distribution for Jump Markov Linear Systems. More specifically, the paper details a novel two-filter smoother that p…
Bayesian Parameter Identification for Jump Markov Linear Systems
Mark P. Balenzuela, Adrian G. Wills, Christopher Renton +1
This paper presents a Bayesian method for identification of jump Markov linear system parameters. A primary motivation is to provide accurate quantification of parameter uncertaint…
Correlated pseudo-marginal Metropolis-Hastings using quasi-Newton proposals
Johan Dahlin, Adrian Wills, Brett Ninness
Pseudo-marginal Metropolis-Hastings (pmMH) is a versatile algorithm for sampling from target distributions which are not easy to evaluate point-wise. However, pmMH requires good pr…