  This paper addresses sensitivity analysis for dynamic models, linking
dependent inputs to observed outputs. The usual method to estimate Sobol
indices are based on the independence of input variables. We present a method
to overpass this constraint when inputs are Gaussian processes of high
dimension in a time related framework. Our proposition leads to a
generalization of Sobol indices when inputs are both dependant and dynamic. The
method of estimation is a modification of the Pick and Freeze simulation
scheme. First we study the general Gaussian cases and secondly we detail the
case of stationary models. We then apply the results to an example of heat
exchanges inside a building.
