86 citations · 192 across the 27 of their papers we have counts for
4 papers · 1 filter
Sequential Markov Chain Monte Carlo for Bayesian Filtering with Massive Data
Allan De Freitas, François Septier, Lyudmila Mihaylova
Advances in digital sensors, digital data storage and communications have resulted in systems being capable of accumulating large collections of data. In the light of dealing with…
Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova
This paper develops a novel sequential Monte Carlo (SMC) approach for joint state and parameter estimation that can deal efficiently with abruptly changing parameters which is a co…
How Can Subsampling Reduce Complexity in Sequential MCMC Methods and Deal with Big Data in Target Tracking?
Allan De Freitas, François Septier, Lyudmila Mihaylova +1
Target tracking faces the challenge in coping with large volumes of data which requires efficient methods for real time applications. The complexity considered in this paper is whe…
Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova
Poyiadjis et al. (2011) show how particle methods can be used to estimate both the score and the observed information matrix for state space models. These methods either suffer fro…