  This working paper considers state-space models where the variance of the
observation is known but the covariance matrix of the state process is unknown
and potentially time-varying. We propose an adaptive algorithm to estimate
jointly the state and the covariance matrix of the state process, relying on
Variational Bayes and second-order Taylor approximations.
