Least squares methods in maximum likelihood problems
The Gauss-Newton algorithm for solving nonlinear least squares problems proves particularly efficient for solving parameter estimation problems when the number of independent observations is large and the fitted model is appropriate. In this context the conventional assumption that the residuals are small is not needed. The Gauss-Newton method is a special case of the Fisher scoring algorithm for maximizing log likelihoods and shares with this a number of desirable properties. The formal...[Show more]
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