  This paper considers the problem of robust adaptive efficient estimating of a
periodic function in a continuous time regression model with the dependent
noises given by a general square integrable semimartingale with a conditionally
Gaussian distribution. An example of such noise is the non-Gaussian
Ornstein-Uhlenbeck-Levy processes. An adaptive model selection procedure, based
on the improved weighted least square estimates, is proposed. Under some
conditions on the noise distribution, sharp oracle inequality for the robust
risk has been proved and the robust efficiency of the model selection procedure
has been established. The numerical analysis results are given.
