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).

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Year of publication:	1985
Authors:	Calzolari, Giorgio ; Panattoni, Lorenzo

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Type of publication:	Book / Working Paper
Language:	English
Notes:	Calzolari, Giorgio and Panattoni, Lorenzo (1985): Gradient methods in FIML estimation of econometric models. Published in: Developments of control theory for economic analysis, ed. by C.Carraro and D.Sartore No. Dordrecht: Martinus Nijhoff, Kluwer Academic Publishers (1987): pp. 143-153.
Classification:	C63 - Computational Techniques ; C3 - Econometric Methods: Multiple/Simultaneous Equation Models
Source:	BASE

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