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From |
Malcolm Wardlaw <malcolm@wardlaw.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Covariance Matrix transform in MLE estimation |

Date |
Wed, 29 Apr 2009 01:09:01 -0500 |

I have a quick question regarding recovering the Hessian variance- covariance matrix in MLE estimation. I've got a mixed bernoulli type log-likelihood function that I'm using the inverselogit(-x-) trick in order to keep Stata from searching for lambda values less than 0 or greater than 1. Essentially telling it to estimate x=logit(-lambda-) instead of -lambda- itself. I know how to ask Stata for the transformed parameter and variance estimate (That is, transforming the logit(-lambda-) estimate into - lambda-. -->nlcom invlogit([logitkappa]_cons). What I need are the covariance terms of the parameters. Essentially the off diagonals of the Hessian matrix (as if I was estimating -lambda- itself along with the other parameters. How do I recover that transformation? Oh, and on a side note, does anyone know why you have to use tricks like that instead of just telling Stata not to search for parameters there? Malcolm * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Covariance Matrix transform in MLE estimation***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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