Gradient methods in FIML estimation of econometric models

Giorgio Calzolari and Lorenzo Panattoni

MPRA Paper from University Library of Munich, Germany

Abstract: 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).

Keywords: Hessian matrix; outer products; maximum likelihood; gradient methods; optimization (search for similar items in EconPapers)
JEL-codes: C3 C63 (search for similar items in EconPapers)
Date: 1985
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Citations: View citations in EconPapers (1)

Published in Developments of control theory for economic analysis, ed. by C.Carraro and D.Sartore Dordrecht: Martinus Nijhoff, Kluwer Academic Publishers (1987): pp. 143-153

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