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...
المؤلفون الرئيسيون: | Andrieu, C, Doucet, A, Tadić, V |
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التنسيق: | Journal article |
اللغة: | English |
منشور في: |
2005
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مواد مشابهة
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On-line parameter estimation in general state-space models using a pseudo-likelihood approach
حسب: Andrieu, C, وآخرون
منشور في: (2012) -
Parameter estimation in general state-space models using particle methods
حسب: Doucet, A, وآخرون
منشور في: (2003) -
Online Expectation-Maximization type algorithms for parameter estimation in general state space models
حسب: Andrieu, C, وآخرون
منشور في: (2003) -
Particle filter as a controlled Markov chain for on-line parameter estimation in general state space models
حسب: Poyiadjis, G, وآخرون
منشور في: (2006) -
Exponential forgetting and geometric ergodicity for optimal filtering in general state-space models
حسب: Tadic, V, وآخرون
منشور في: (2005)