Parameter estimation in general state-space models using particle methods
Particle filtering techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. If the model includes fixed parameters, a standard technique to perform parameter estimation consists of extending the state wi...
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| Format: | Conference item |
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2003
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