A New Approach to Drawing States in State Space Models
We introduce a new method for drawing state variables in Gaussian state space models from their conditional distribution given parameters and observations. Unlike standard methods, our method does not involve Kalman filtering. We show that for some important cases, our method is computationally more efficient than standard methods in the literature. We consider two applications of our method.
|Date of creation:||2007|
|Date of revision:|
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- J. Durbin, 2002. "A simple and efficient simulation smoother for state space time series analysis," Biometrika, Biometrika Trust, vol. 89(3), pages 603-616, August.
- repec:oup:restud:v:65:y:1998:i:3:p:361-93 is not listed on IDEAS
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