Polson, Nicholas G.; Roberts, Gareth O. - In: Stochastic Processes and their Applications 48 (1993) 2, pp. 341-356
A Bayesian perspective is taken to quantify the amount of information learned from observing a stochastic process, Xt, on the interval [0, T] which satisfies the stochastic differential equation, dXt = S([theta], t, Xt)dt+[sigma](t, Xt)dBt. Information is defined as a change in expected utility...