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From |
Matthew Wibbenmeyer <[email protected]> |

To |
[email protected] |

Subject |
st: -ml- programming for conditional logit |

Date |
Tue, 17 May 2011 14:04:26 -0600 |

Greetings, I am working on building a maximum likelihood estimator for conditional logit, with the hopes that it can be modified to accommodate the estimate a non-linear utility function using a choice experiment data set. So far, I have written a method d0 program (see below) that matches results from the 'canned' conditional logit. However, I would like to develop a method d2 program that will run more reliably and efficiently on more complex utility functions. Would anyone with experience coding d2 method conditional logit estimators be willing to share their methods for coding the gradient and Hessian? Specifically my confusion comes from how to code the vector of explanatory variables (not the coefficients), which enters into the formula for the conditional logit gradient function. Greene (1997) writes the gradient function as: g = sum_{i=1,n} sum_{j=1,J} d_ij*(x_ij - xbar_i) where d_ij = 1 if y_i = j and 0 otherwise, and where xbar_i = sum_{j=1,J} P_ij*x_ij x_ij is a vector of values for the explanatory variables in a particular observation, and it is unclear to me how to code this within my ml estimator. Thank you for your help, Matt Wibbenmeyer USDA Forest Service Rocky Mountain Research Station PO Box 7669 200 E. Broadway Missoula, MT 59807 --------------------------------------------------------------------------------------------- program myclog args todo b lnf g negH tempvar denom p b1 mleval `b1' = `b', eq(1) qui { egen double `denom' = sum(exp(`b1')), by(obsid) gen double `p' = exp(`b1')/`denom' mlsum `lnf' = $ML_y1*log(`p') if $ML_y1==1 if (`todo'==0 | `lnf'>=.) exit } end ml model d0 myclog (Eq1: choice = x1 x2 x3, nocons) ml search ml max --------------------------------------------------------------------------------------------- * * 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/

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