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From |
Jonathan Hanson <johanson@maxwell.syr.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: vector of independent variables in ML program |

Date |
Tue, 12 Aug 2008 09:59:16 -0400 |

Dear Stas, Thanks for the reply. I have an earlier edition of the Gould et. al. book and agree that it is helpful. Nothing in there, however, pertaining to my question, at least in the edition I have. I would definitely rather not write the gradient vector, but my model is complex and the lf method of estimation is not working for me. As I work through the derivatives, it seems that I have vectors of independent variables that need to be called directly, hence my question. Thanks again, Jon On Aug 12, 2008, at 9:47 AM, Stas Kolenikov wrote: > A big idea of -ml- is that you don't have to do that, as the > derivatives with respect to beta's necessary for likelihood > maximization and variance estimation will be computed by the chain > rule. If all that your equations depend on is theta, then you don't > really need to go into x's. The book on [ML] will explain all the > details (http://www.stata.com/bookstore/mle.html), and if you write > your own -ml- code, that book is a must. > > On Tue, Aug 12, 2008 at 8:29 AM, Jonathan Hanson > <johanson@maxwell.syr.edu> wrote: >> Greetings, >> >> How does one refer to a vector of independent variables from within >> an ML >> program? For example, suppose I need to write a gradient vector, the >> formula for which looks something like this: >> >> ∂ ln L/ ∂ Β = (1/sigma^2) x'(y - xΒ) >> >> where x' is a k by 1 vector of the independent variables for an >> observation. >> I know that I can refer to y as $ML_y1 and xB as one of the arguments >> (theta, for instance), but how can I call x' in the formula? >> Ultimately, I >> will have multiple equations in this formula, so I need to be able to >> specify equation from which the x's are coming. >> >> Many thanks, >> >> >> >> Jonathan Hanson >> Assistant Professor of Political Science >> Maxwell School of Citizenship and Public Affairs >> 100 Eggers Hall >> Syracuse University >> Syracuse, NY 13244 >> >> >> >> >> >> * >> * 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/ >> > > > > -- > 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/ _______________________________________ Jonathan Hanson Assistant Professor of Political Science Maxwell School of Citizenship and Public Affairs 100 Eggers Hall Syracuse University Syracuse, NY 13244 johanson@maxwell.syr.edu * * 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: vector of independent variables in ML program***From:*"Stas Kolenikov" <skolenik@gmail.com>

**References**:**st: vector of independent variables in ML program***From:*Jonathan Hanson <johanson@maxwell.syr.edu>

**Re: st: vector of independent variables in ML program***From:*"Stas Kolenikov" <skolenik@gmail.com>

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