On sequential estimation of the mean of a multidimensional gaussian process

For a multidimensional continuous time GAUssian process whose mean vector depends linearly of a multidimensional parameter, we consider a sequential estimation niodel. A suitable estimator process is constructed, and its distributions are analyzed in order to prove that it is progressively sufficient, After the reduction by sufficiency, an invariant structure is introduced and the optimal invariant terminal decision function is obtained.