Approximate maximum likelihood estimation in linear regression |
| |
Authors: | Michael A Magdalinos |
| |
Institution: | (1) Department of Statistics and Information Science, The Athens University of Economics and Business, 76, Patission Street, 104 34 Athens, Greece |
| |
Abstract: | 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(v
i
) asv 0 fori>0.Research financed in part by the Research Center of the Athens University of Economics and Business. |
| |
Keywords: | Regression maximum likelihood non-normal errors Edgeworth approximation |
本文献已被 SpringerLink 等数据库收录! |