Resumo

ARENAS, Favián; MARTINEZ, Héctor Jairo  e  PEREZ, Rosana. Structured BFGS Method for the Estimation of the Maximum Likelihood. rev. cienc. [online]. 2016, vol.20, n.2, pp.39-54. ISSN 0121-1935.  https://doi.org/10.25100/rc.v20i2.4672.

Given the special structure of the Hessian matrix of the log-likelihood function which is parallel to that found in nonlinear least-squares problems, we introduce the structured BFGS secant method for the maximum-likelihood estimation and for the development or the local and super-linear convergence theory for the algorithm, following the lines of Martínez; Martínez and Egels, and the theory about maximum-likelihood estimation given in Gonglewski. We present the results of some numerical experiments which show a good performance of our algorithm.

Palavras-chave : maximum likelihood estimation; likelihood function; structured secant method; nonlinear least‐squares problem; super-linear convergence.

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