On-line parameter estimation in general state-space models
The estimation of static parameters in general non-linear non-Gaussian state-space models is a long-standing problem. This is despite the advent of Sequential Monte Carlo (SMC, aka particle filters) methods, which provide very good approximations to the optimal filter under weak assumptions. Several...
Prif Awduron: | Andrieu, C, Doucet, A, Tadić, V |
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Fformat: | Journal article |
Iaith: | English |
Cyhoeddwyd: |
2005
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Eitemau Tebyg
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On-line parameter estimation in general state-space models using a pseudo-likelihood approach
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Parameter estimation in general state-space models using particle methods
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Particle filter as a controlled Markov chain for on-line parameter estimation in general state space models
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Exponential forgetting and geometric ergodicity for optimal filtering in general state-space models
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