Detail publikace

Rao-Blackwellized particle Gibbs kernels for smoothing in jump Markov nonlinear models

PAPEŽ, M.

Originální název

Rao-Blackwellized particle Gibbs kernels for smoothing in jump Markov nonlinear models

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Jump Markov nonlinear models (JMNMs) characterize a dynamical system by a finite number of presumably nonlinear and possibly non-Gaussian state-space configurations that switch according to a discrete-valued hidden Markov process. In this context, the smoothing problem - the task of estimating fixed points or sequences of hidden variables given all available data -is of key relevance to many objectives of statistical inference, including the estimation of static parameters. The present paper proposes a particle Gibbs with ancestor sampling (PGAS)-based smoother for JMNMs. The design methodology relies on integrating out the discrete process in order to increase the efficiency through Rao-Blackwellization. The experimental evaluation illustrates that the proposed method achieves higher estimation accuracy in less computational time compared to the original PGAS procedure.

Klíčová slova

Sequential Monte Carlo; particle filtering; particle smoothing; particle Markov chain Monte Carlo; particle Gibbs with ancestor sampling; jump Markov nonlinear models; Rao-Blackwellization

Autoři

PAPEŽ, M.

Vydáno

12. 6. 2018

Nakladatel

Institute of Electrical and Electronics Engineers (IEEE)

ISBN

9783952426999

Kniha

Proceedings of the 16th European Control Conference, ECC 2018

Strany od

2466

Strany do

2471

Strany počet

6

BibTex

@inproceedings{BUT148840,
  author="Milan {Papež}",
  title="Rao-Blackwellized particle Gibbs kernels for smoothing in jump Markov nonlinear models",
  booktitle="Proceedings of the 16th European Control Conference, ECC 2018",
  year="2018",
  pages="2466--2471",
  publisher="Institute of Electrical and Electronics Engineers (IEEE)",
  doi="10.23919/ECC.2018.8550408",
  isbn="9783952426999"
}