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


From   Nick Cox <[email protected]>
To   [email protected]
Subject   Re: st: change the format of the pseudo log-likelihood in gb2fit
Date   Fri, 6 Jul 2012 19:18:55 +0100

The last bit involves taking logarithms of some slightly messy
expressions. That's all.

On your first point, I don't understand what you are missing. If the
final log-likelihoods for different models are the same to 4
significant figures, I suggest that they are to be regarded as
identical in practice. Alternatively, I guess that least one of the
following statements is true.

1. You didn't try my suggestion of using -display- with a different
format on r(sum).

2. You did try it, but ran into some problem, in which case you need
to spell out what that problem is.

3. You want something else, but again you need to spell out what that
is. That said, it seems very unlikely that anyone will rewrite these
programs for you.

Nick

On Fri, Jul 6, 2012 at 6:59 PM, Lucia R.Latino
<[email protected]> wrote:
> Dear Nick,
>
> thanks for your hint.
>
> I am trying to compare different nested distributions and  I would love to
> compare the log likelihood. With the scientific notation I cannot see any
> difference. That is the reason why I was trying to obtain the full log
> likelihood.
>
> Combine Michael's code and -display- I am able to get the full log
> likelihood. But I haven't been able to change how stata display the result
> after gb2fit or similar command.
>
> Does anyone can help me in writing the explicit expression for
> log-likelihood for lognfit, dagumfit, smfit, fisk and Beta2 similar to what
> Michal wrote for the gb2fit?
>
> Thanks,
> Lucia
>
> -----Messaggio originale-----
> Da: [email protected]
> [mailto:[email protected]] Per conto di Nick Cox
> Inviato: venerdì 6 luglio 2012 11:58
> A: [email protected]
> Oggetto: Re: st: change the format of the pseudo log-likelihood in gb2fit
>
> -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
> <[email protected]> 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: [email protected]
>> [mailto:[email protected]] Per conto di Michal
>> Brzezinski
>> Inviato: giovedì 5 luglio 2012 23:15
>> A: [email protected]
>> 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 <[email protected]>:
>>> 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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