A novel parameterization of state-transition distributions enables maximum-likelihood and score-matching estimators for joint recovery of linear dynamics and noise covariance that outperform ordinary least squares.
Ljung, On the consistency of prediction error identification methods, in: Mathematics in Science and Engineering, volume 126, Elsevier, 1976, pp
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Joint Identification of Linear Dynamics and Noise Covariance via Distributional Estimation
A novel parameterization of state-transition distributions enables maximum-likelihood and score-matching estimators for joint recovery of linear dynamics and noise covariance that outperform ordinary least squares.