  The paper considers the problem of estimating the parameters in a continuous
time regression model with a non-Gaussian noise of pulse type. The noise is
specified by the Ornstein-Uhlenbeck process driven by the mixture of a Brownian
motion and a compound Poisson process. Improved estimates for the unknown
regression parameters, based on a special modification of the James-Stein
procedure with smaller quadratic risk than the usual least squares estimates,
are proposed. The developed estimation scheme is applied for the improved
parameter estimation in the discrete time regression with the autoregressive
noise depending on unknown nuisance parameters.
