  The problems of the construction of the asymptotically distribution free
goodness-of-fit tests for three models of stochastic processes are considered.
The null hypothesis for all models is composite parametric. All tests are based
on the score-function processes, where the unknown parameter is replaced by the
MLE. We show that a special change of time transforms the limit score-function
processes into the Brownian bridge. This property allows us to construct the
asymptotically distribution free tests for the following three models of
stochastic processes : dynamical systems with small noise, ergodic diffusion
processes, inhomogeneous Poisson processes and nonlinear AR time series.
