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From |
Stas Kolenikov <skolenik@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: "brute force" procedure for ml init |

Date |
Mon, 8 Mar 2010 13:13:13 -0600 |

On Mon, Mar 8, 2010 at 12:20 PM, Ian Breunig <ianbreunig@gmail.com> wrote: > I need to conduct a "brute force" procedure to search for initial > parameter values for a MLE with a relatively large amount of > parameters. I'd like to to be able to use some sort of loop with a > program to do this. For example, I believe that I would like to start > by randomly drawing (kx1) starting values using a random number > generator for a uniform distribution on the unit interval (can I do > this using the "ml init" command?), then maximize. Then repeat this > process several times. How about this: local q = # of random starts local p = dimension of the parameter vector forvalues i=1/`q' { matrix from = J(1,`p',0) forvalues j = 1/`p' { matrix from[1,`j'] = uniform() } ml <definition with the name of the evaluator, etc.> ml trace on ml init from, copy ml search * if you like ml maximize } If you believe your surface looks weird with many narrow peaks, then the asymptotic theory that yields normality of the estimates is hardly applicable. You'd still be able to get some sort of estimates, but (i) you don't really know which of the local maxima gives rise to consistent estimates, and (ii) you won't be able to conduct inference with asymptotic standard errors and chi-square tests. -- Stas Kolenikov, also found at http://stas.kolenikov.name Small print: I use this email account for mailing lists only. * * 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/

**References**:**st: "brute force" procedure for ml init***From:*Ian Breunig <ianbreunig@gmail.com>

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