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Numerical algorithms for constrained maximum likelihood estimation

Li, Zheng Feng; Osborne, Michael; Prvan, Tania


This paper describes a SQP-type algorithm for solving a constrained maximum likelihood estimation problem that incorporates a number of novel features. We call it MLESOL. MLESOL maintains the use of an estimate of the Fisher information matrix to the Hessian of the negative log-likelihood but also encompasses a secant approximation S to the second-order part of the augmented Lagrangian function along with tests for when to use this information. The local quadratic model used has a form...[Show more]

CollectionsANU Research Publications
Date published: 2003
Type: Journal article
Source: Australian and New Zealand Industrial and Applied Mathematics
DOI: 10.1017/S1446181100013171


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