Abstract
This paper develops a method to evaluate the smoothed estimator of the disturbance vector in a state space model together with its mean squared error matrix. This disturbance smoother also leads to an efficient smoother for the state vector. Applications include a method to calculate auxiliary residuals for unobserved components time series models and an EM algorithm for estimating covariance parameters in a state space model.
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