Fast smoothing in switching approximations of non-linear and non-Gaussian models-Reference-Cited by-同舟云学术

Fast smoothing in switching approximations of non-linear and non-Gaussian models

Published:2017-10 Issue: Volume:114 Page:38-46
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Gorynin Ivan,Derrode Stéphane^ORCID,Monfrini Emmanuel,Pieczynski Wojciech

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference27 articles.

1. Optimal filter approximations in conditionally Gaussian pairwise Markov switching models;Abbassi;IEEE Trans. Automat. Control,2015

2. Bao, Y., Chiarella, C., Kang, B., 2012. Particle filters for Markov switching stochastic volatility models, Research Paper Series 299, Quantitative Finance Research Centre, University of Technology, Sydney.

3. Smoothing algorithms for state-space models;Briers;Ann. Inst. Statist. Math.,2010

4. Inference in Hidden Markov Models;Cappé,2005

5. Dynamic Bayesian beta models;Da-Silva;Comput. Statist. Data Anal.,2011

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