Abstract
The recursive least squares (RLS) identification algorithm with a forgetting factor is often used to estimate time-varying parameters in stochastic systems. It is however hard to say anything about the distribution of the parameter estimates, since they are non-linear functions of the observations. In this paper we present a way to compute the exact distribution and moments of the weighted least squares (WLS)-estimator in a time-varying Gaussian AR(1)-process. The RLS-estimate follows as special case of the WLS-estimator.
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