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I asked a related question here:

How to apply Levenberg Marquardt to Max Likelihood Estimation

I tried the approach suggested it works for some of the parameters but not the variances. I spoke to the author of the paper and he said he used Eviews to do the analysis, and that Eviews has a function that allows maxlikelihood estimation via the Marquardt algorithm.

Given that the Marquardt algorithm is generally used to solve least square type problems what is Eviews doing to allow it to be applied to maximum likelihood problems?

1.) Does it change the Marquardt algorithm? If so how?

2.) Does it reformulate the log likelihood maximization as a least squares problem? If so how?

Baz

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Do you have documentation for eviews ? –  lmorin Jul 15 at 10:05
    
Only what's online which is not very detailed. –  Bazman Jul 15 at 14:16

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