Online expectation-maximization type algorithms for parameter estimation in general state space models
We present new online algorithms to estimate static parameters in nonlinear non-Gaussian state space models. These algorithms rely on online expectation-maximization (EM) type algorithms. Contrary to standard sequential Monte Carlo (SMC) methods recently proposed in the literature, these algorithms do not degenerate over time.