Gradient methods in FIML estimation of econometric models

Through Monte Carlo experiments, this paper compares the performances of different gradient optimization algorithms, when performing full information maximum likelihood (FIML) estimation of econometric models. Different matrices are used (Hessian, outer products matrix, GLS-type matrix, as well as a mixture of them).

MoreLess

Year of publication:	1985
Authors:	Calzolari, Giorgio ; Panattoni, Lorenzo
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Hessian matrix \| outer products \| maximum likelihood \| gradient methods \| optimization

freely available

Full text |

More access options

Check Google Scholar

In German libraries (KVK)

I need help

More details

Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C63 - Computational Techniques ; C3 - Econometric Methods: Multiple/Simultaneous Equation Models
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008565138