This paper introduces a new method for online estimation and predictionof states and parameters of nonlinear stochastic differential equations. Inthis setup parameters are considered as random variables in a Bayesiansense, which requires integration over parameter distributions. This...

Linear stochastic dierential equations (SDE) are expressed as an exactdiscrete model (EDM) and estimated with structural equation models(SEM) and the Kalman lter (KF) algorithm. The SEM likelihood is welldened even for the times series case and the SEM and KF approach yieldthe same likelihood....