Estimation of structural changes in nonlinear time series models by using particle filters and genetic programming
Author:
Affiliation:
1. College of Economics and Management; China Agricultural University; Beijing 100083 China
2. Graduate School of Economics; Kyushu University; Fukuoka 812-8581 Japan
Funder
Humanity and Social Science Foundation of Ministry of Education of China
Publisher
Wiley
Subject
Electrical and Electronic Engineering,Signal Processing,Control and Systems Engineering
Link
http://onlinelibrary.wiley.com/wol1/doi/10.1002/acs.2578/fullpdf
Reference39 articles.
1. Particle filters for state estimation of jump Markov linear systems;Doucet;IEEE Transactions on Signal Processing,2001
2. Sequential Monte Carlo Methods in Practice
3. Particle filters for positioning, navigation, and tracking;Gustafsson;IEEE Transactions on Signal Processing,2002
4. Gaussian sum particle filtering;Kotecha;IEEE Transactions on Signal Processing,2003
5. Marginalized particle filters for mixed linear/nonlinear state-space models;Schon;IEEE Transactions on Signal Processing,2005
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