Leitura do Dia - The Devil is in the Detail: Hints for Practical Optimisation
The Devil is in the Detail: Hints for Practical Optimisation
T M Christensen, A S Hurn and K A Lindsay
Finding the minimum of an objective function, such as a least squares or negative log-likelihood function, with respect to the unknown model parameters is a problem often encountered in econometrics. Consequently, students of econometrics and applied econometricians are usually well-grounded in the broad differences between the numerical procedures employed to solve these problems. Often, however, relatively little time is given to understanding the practical subtleties of implementing these schemes when faced with illbehaved problems. This paper addresses some of the details involved in practical optimisation, such as dealing with constraints on the parameters, specifying starting values, termination criteria and analytical gradients, and illustrates some of the general ideas with several instructive examples.
Qualquer que já tenha trabalhado com otimização numérica sabe que existem muitos detalhes importantes. Esse interessante artigo detalha alguns destes problemas, como a escolha de valores iniciais e o uso de transformações de parâmetros para impor restrições.
Muito bem escrito e útil.
T M Christensen, A S Hurn and K A Lindsay
Finding the minimum of an objective function, such as a least squares or negative log-likelihood function, with respect to the unknown model parameters is a problem often encountered in econometrics. Consequently, students of econometrics and applied econometricians are usually well-grounded in the broad differences between the numerical procedures employed to solve these problems. Often, however, relatively little time is given to understanding the practical subtleties of implementing these schemes when faced with illbehaved problems. This paper addresses some of the details involved in practical optimisation, such as dealing with constraints on the parameters, specifying starting values, termination criteria and analytical gradients, and illustrates some of the general ideas with several instructive examples.
Qualquer que já tenha trabalhado com otimização numérica sabe que existem muitos detalhes importantes. Esse interessante artigo detalha alguns destes problemas, como a escolha de valores iniciais e o uso de transformações de parâmetros para impor restrições.
Muito bem escrito e útil.
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