The standard continuous time state space model with stochastic disturbances
contains the mathematical abstraction of continuous time white noise. To work with well
defined,
discrete time observations, it is necessary to sample the model with care. The basic
issues are
well known, and have been discussed in the literature. However, the consequences have
not
quite penetrated the practise of estimation and identification. One example is that the
standard
model of an observation being a snapshot of the current state plus noise independent of
the
state cannot be reconciled with this picture. Another is that estimation and identification
of
time continuous models require a more careful treatment of the sampling formulas. We
discuss
and illustrate these issues in the current contribution. An application of particular
practical
importance is the estimation of models based on irregularly sampled observations.