Re: st: change the format of the pseudo log-likelihood in gb2fit

[Nick Cox <njcoxstata@gmail.com>]

-gb2fit- is a user-written program from SSC written by Stephen Jenkins.

-display- takes a format which can be used to change how a result is
displayed. Look at the help for -display- and for -format-. However,
it is difficult to see that further decimal places could be of either
use or interest.

Nick

On Fri, Jul 6, 2012 at 10:41 AM, Lucia R.Latino
<Latino@economia.uniroma2.it> wrote:
> Dear Michal and Stephen,
>
> Thanks for your answer. I tried Michal's code and it actually recovers the
> log pseudolikelihood, however stata shows the value using again the
> scientific notation. Do you have any suggestion?
> Furthermore, I am not sure I am able to write the same code for the other
> distributions I am using (lognfit, smfit, dagumfit, fisk, beta2). Do you
> think there is a way to simply change the format of the Iteration so to have
> more precision?
>
> If it can helps I copied the result I obtained.
>
> Thanks,
> Lucia
>
> -----------------------------------------------------------start output
> ----------------------------------------------------------------------------
> ------------
> gb2fit dec_ae, cdf(gb2cdf) pdf(gb2pdf) svy
>
> initial:       log pseudolikelihood =     -<inf>  (could not be evaluated)
> feasible:      log pseudolikelihood = -1.469e+08
> rescale:       log pseudolikelihood = -1.469e+08
> rescale eq:    log pseudolikelihood = -1.075e+08
> Iteration 0:   log pseudolikelihood = -1.075e+08  (not concave)
> Iteration 1:   log pseudolikelihood = -1.064e+08  (not concave)
> Iteration 2:   log pseudolikelihood = -1.063e+08
> Iteration 3:   log pseudolikelihood = -1.060e+08  (not concave)
> Iteration 4:   log pseudolikelihood = -1.060e+08
> Iteration 5:   log pseudolikelihood = -1.059e+08
> Iteration 6:   log pseudolikelihood = -1.059e+08
> Iteration 7:   log pseudolikelihood = -1.059e+08
> Iteration 8:   log pseudolikelihood = -1.059e+08
> Iteration 9:   log pseudolikelihood = -1.059e+08
> Iteration 10:  log pseudolikelihood = -1.059e+08
> Iteration 11:  log pseudolikelihood = -1.059e+08
> Iteration 12:  log pseudolikelihood = -1.059e+08
>
> ML fit of GB2 distribution
>
> pweight:  iwght                                   Number of obs    =
> 11183
> Strata:   <one>                                   Number of strata =
> 30
> PSU:      <observations>                          Number of PSUs   =
> 564
>                                                   Population size  =
> 12272397
>                                                   F(   0,    535)  =
> .
>                                                   Prob > F         =
> .
>
> ----------------------------------------------------------------------------
> --
>       dec_ae |      Coef.   Std. Err.      t    P>|t|     [95% Conf.
> Interval]
> -------------+--------------------------------------------------------------
> --
> a            |
>        _cons |   2.327935   .2782045     8.37   0.000     1.781426
> 2.874444
> -------------+--------------------------------------------------------------
> --
> b            |
>        _cons |   3997.361   250.2252    15.98   0.000     3505.814
> 4488.907
> -------------+--------------------------------------------------------------
> --
> p            |
>        _cons |   1.603659   .2993526     5.36   0.000     1.015606
> 2.191712
> -------------+--------------------------------------------------------------
> --
> q            |
>        _cons |   2.983855   .6731986     4.43   0.000     1.661412
> 4.306297
> ----------------------------------------------------------------------------
> --
>
>  tempvar ll
> local wv= "`e(wvar)'"
>
>  gen `ll' = lngamma(e(bp)+e(bq)) + log(e(ba)) + (e(ba)*e(bp)-1)* log(dec_ae)
> ///
>          - e(ba)*e(bp)*log(e(bb)) - lngamma(e(bp)) - lngamma(e(bq)) - ///
>          (e(bp)+e(bq))*log(1+(dec_ae/e(bb))^e(ba))
>
>  qui sum `ll' [aw=`wv'] if e(sample),meanonly
> di r(sum)
>
> -1.059e+08
> -----------------------------------------------------------end output
> ----------------------------------------------------------------------------
> ------------
>
> Lucia
>
>
> -----Messaggio originale-----
> Da: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] Per conto di Michal Brzezinski
> Inviato: giovedì 5 luglio 2012 23:15
> A: statalist@hsphsun2.harvard.edu
> Oggetto: Re: st: change the format of the pseudo log-likelihood in gb2fit
>
> You can recover pseudo log-likelihood writing an explicit expression for
> log-likelihood for a given model.
> For example, in case of GB2 model you could try the following code:
>
> gb2fit dec, cdf(gb2cdf) pdf(gb2pdf) svy
> tempvar ll
> local wv= "`e(wvar)'"
>
> gen `ll' = lngamma(e(bp)+e(bq)) + log(e(ba)) + (e(ba)*e(bp)-1)* log(dec) ///
>         - e(ba)*e(bp)*log(e(bb)) - lngamma(e(bp)) - lngamma(e(bq)) - ///
>         (e(bp)+e(bq))*log(1+(dec/e(bb))^e(ba))
> qui sum `ll' [aw=`wv'] if e(sample),meanonly di r(sum)
>
> ----------
> Hope this helps,
> Michal
>
> 2012/7/5 Lucia Latino <Latino@economia.uniroma2.it>:
>> Dear Statalist,
>>
>> After running - gb2fit - smfit - lognfit - Stata reports the pseudo
>> log-likelihood with the scientific notation, but I want to view the
>> full likelihood.
>> Usually, I can obtain the full log-likelihood by using - display e(ll)
>> -
>>
>> However, I need to add the option svy for the estimation (e.g. -
>> gb2fit dec, stats cdf(gb2cdf) pdf(gb2pdf) svy - ) and after adding the
>> option 'svy', Stata doesn't store anymore the pseudo log-likelihood in
> e(ll).
>>
>> Is there any way to do change the format of the pseudo log-likelihood
>> in the iterations or a way to obtain it after the estimation?

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