Gradient methods in FIML estimation of econometric models

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.

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).

• Item Type: MPRA Paper
• Language: English
• Keywords: Hessian matrix; outer products; maximum likelihood; gradient methods; optimization
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables

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