Efficient Particle MCMC with GMM Likelihood Representation

2019 ◽  
Author(s):  
Fabio Franco
Keyword(s):  
Particle Mcmc

scholarly journals Parallel Implementation of Particle MCMC Methods on a GPU*

2012 ◽  
Vol 45 (16) ◽  
pp. 1143-1148 ◽  
Author(s):  
Soren Henriksen ◽  
Adrian Wills ◽  
Thomas B. Schön ◽  
Brett Ninness
Keyword(s):  
Parallel Implementation ◽  
Mcmc Methods ◽  
Particle Mcmc

scholarly journals Augmentation schemes for particle MCMC

2015 ◽  
Vol 26 (6) ◽  
pp. 1293-1306 ◽  
Author(s):  
Paul Fearnhead ◽  
Loukia Meligkotsidou
Keyword(s):  
Particle Mcmc

scholarly journals Uncertainty modelling and computational aspects of data association

2021 ◽  
Vol 31 (5) ◽  
Author(s):  
Jeremie Houssineau ◽  
Jiajie Zeng ◽  
Ajay Jasra
Keyword(s):  
Markov Models ◽  
Hidden Markov ◽  
Possibility Theory ◽  
Uncertainty Modelling ◽  
Alternative Representation ◽  
Lack Of Information ◽  
Partially Observed ◽  
Computational Aspects ◽  
Particle Mcmc ◽  
Filtering Problem

AbstractA novel solution to the smoothing problem for multi-object dynamical systems is proposed and evaluated. The systems of interest contain an unknown and varying number of dynamical objects that are partially observed under noisy and corrupted observations. In order to account for the lack of information about the different aspects of this type of complex system, an alternative representation of uncertainty based on possibility theory is considered. It is shown how analogues of usual concepts such as Markov chains and hidden Markov models (HMMs) can be introduced in this context. In particular, the considered statistical model for multiple dynamical objects can be formulated as a hierarchical model consisting of conditionally independent HMMs. This structure is leveraged to propose an efficient method in the context of Markov chain Monte Carlo (MCMC) by relying on an approximate solution to the corresponding filtering problem, in a similar fashion to particle MCMC. This approach is shown to outperform existing algorithms in a range of scenarios.

scholarly journals A generalized Schwartz model for energy spot prices — Estimation using a particle MCMC method

2018 ◽  
Vol 72 ◽  
pp. 560-582 ◽  
Author(s):  
Anne Floor Brix ◽  
Asger Lunde ◽  
Wei Wei
Keyword(s):  
Mcmc Method ◽  
Spot Prices ◽  
Particle Mcmc

scholarly journals Particle MCMC algorithms and architectures for accelerating inference in state-space models

2017 ◽  
Vol 83 ◽  
pp. 413-433 ◽  
Author(s):  
Grigorios Mingas ◽  
Leonardo Bottolo ◽  
Christos-Savvas Bouganis
Keyword(s):  
State Space ◽  
State Space Models ◽  
Mcmc Algorithms ◽  
Particle Mcmc
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