Sequential inference of parameters is performed using Bayesian updating, which is available in closed form when independent gamma priors are assumed, and the current system state is known. For the two sampled transitions, the associated parameters are updated in a manner that is consistent with how information is gained during sampling so that the rate of information gain is proportional to the sampling rate.