Estimation for finite parameter schemes

The object is to indicate the character of results for the approximate maximum likelihood estimation of parameters in nonminimum phase nonGaussian finite parameter schemes. The estimates are asymptotically normal under appropriate smoothness and positivity conditions on the probability density function of the generating independent random variables. The character of the asymptotic covariance matrix is indicated. In the truly nonminimum phase nonGaussian case one does not have consistency using the classical estimates using a Gaussian likelihood.