Approximate maximum likelihood estimation in linear regression

The application of the ML method in linear regression requires a parametric form for the error density. When this is not available, the density may be parameterized by its cumulants (_i) and the ML then applied. Results are obtained when the standardized cumulants (_i) satisfy _i=_i+2/₂^(i+2)/2=O(vⁱ) asv 0 fori>0.Research financed in part by the Research Center of the Athens University of Economics and Business.