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From |
Matthew Baker <matthew.baker@hunter.cuny.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: MLE for Tobit I |

Date |
Mon, 24 Oct 2011 13:11:30 -0400 |

Alba, I'm wondering if this doesn't have something to do with the nature of the data, or if the problem isn't occurring somewhere else. What is the exact error message or output you receive when you try and run the above? I was able to get the function to work in version 11.2 as follows. /* Begin example */ clear all set seed 5150 set obs 1000 gen x=invnormal(runiform()) scalar mu=.5 scalar beta=.3 gen e=invnormal(runiform()) gen y=mu+beta*x+e gen y1=y replace y1=0 if y<=0 capture program drop mytobit1 program mytobit1 version 10.1 args lnf beta sigma quietly replace `lnf'= log(1-normal(`beta'/`sigma')) if $ML_y1==0 quietly replace `lnf'= log((1/`sigma')*normalden(($ML_y1-`beta')/`sigma')) if $ML_y1>0 end ml model lf mytobit1 (y1 = x) /sigma ml check ml maximize, nolog / * End example */ For this example, I get the output: initial: log likelihood = -<inf> (could not be evaluated) feasible: log likelihood = -1820.7288 rescale: log likelihood = -1382.4015 rescale eq: log likelihood = -1272.0074 Iteration 0: log likelihood = -1272.0074 Iteration 1: log likelihood = -1243.0683 Iteration 2: log likelihood = -1240.0485 Iteration 3: log likelihood = -1240.0446 Iteration 4: log likelihood = -1240.0446 Number of obs = 1000 Wald chi2(1) = 63.71 Log likelihood = -1240.0446 Prob > chi2 = 0.0000 ------------------------------------------------------------------------------ y1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] -------------+---------------------------------------------------------------- eq1 | x | .2609818 .0326973 7.98 0.000 .1968964 .3250673 _cons | .5116592 .0336745 15.19 0.000 .4456584 .57766 -------------+---------------------------------------------------------------- sigma | _cons | .9906555 .0285645 34.68 0.000 .9346701 1.046641 ------------------------------------------------------------------------------ . So things seem to be working... Best, Matt Baker On Mon, Oct 24, 2011 at 12:27 PM, Alba J. Collart-Dinarte <ACollart@ag.tamu.edu> wrote: > Dear Stata listers, > > I have a question about programming the likelihood function for Tobit models (type I, censored at zero) in STATA 10.1. This is the code I've written: > > program mytobit1 > version 10.1 > args lnf beta sigma > quietly replace `lnf'= log(1-normal(`beta'/`sigma')) if $ML_y1==0 > quietly replace `lnf'= log((1/`sigma')*normalden(($ML_y1-`beta')/`sigma')) if $ML_y1>0 > end > > ml model lf mytobit1 (y1 = x) /sigma > ml check > ml maximize, nolog > > but it does not run. I believe that there is a problem in the way I define the likelihood function. I have looked into Gould, Pitblado and Poi (2010), but they mainly discuss probit, normal and weibull models. > > I have also tried: > quietly replace `lnf'= cond($ML_y1==0,log(1-normal(`beta',`sigma')),log((1/`sigma')*normalden($ML_y1,`beta',`sigma'))) > and using normalden($ML_y1,`beta',`sigma') - instead of - normalden(($ML_y1-`beta')/`sigma') > but no success. > > Any suggestions on how can I fix the code would be greatly appreciated. > > Thank you very much in advance! > > Alba Collart > * > * 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/ > -- Dr. Matthew J. Baker Department of Economics Hunter College and the Graduate Center, CUNY * * 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: MLE for Tobit I***From:*"Alba J. Collart-Dinarte" <ACollart@ag.tamu.edu>

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