Parameter Estimation in General State-Space Models using Particle Methods

@inproceedings{Doucet2003ParameterEI,
  title={Parameter Estimation in General State-Space Models using Particle Methods},
  author={Arnaud Doucet and Vladislav B. Tadic},
  year={2003}
}
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 with the parameter to transform the problem into an optimal filtering problem. However, this approach requires the use of special particle filtering techniques which suffer from several drawbacks. We… CONTINUE READING
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