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Re: st: Problem with ML estimation
I am not sure I understand your comment. I am trying to estimate two parameters (both constants) and not four. These constants are those contained in `theta3' and `theta5'. Since I have three distinct observations, the model should work. Or am I missing something?
I can ofcourse analytically see that the result of the estimation should give me `theta3' as +\infty (or a very large number). Would it be a problem for STATA if the result is +\infty?
Deepankar
----- Original Message -----
From: Stas Kolenikov <[email protected]>
Date: Friday, August 18, 2006 11:02 am
Subject: Re: st: Problem with ML estimation
> Your model is underidentified. You have three distinct observations,
> and you are trying to estimate four parameters.
>
> On 8/17/06, DEEPANKAR BASU <[email protected]> wrote:
> > Hi!
> >
> > I am trying to run a MLE on a small data set that I have
> generated on my own; this is primarily to check the program. When I
> run the program I get an error message saying "could not calculate
> numerical derivatives; missing values encountered". Below I give
> (in that order):
> > 1) the data generation program
> > 2) the ML program
> > 3) output of the ML program
> >
> > Any help to get the program running will be greatly appreciated.
> >
> > Thanks in advance.
> >
> > Deepankar
> >
> > =============india31A.do=================
> > clear
> > set more 1
> > version 8.2
> >
> > set obs 4000
> >
> > gen dfsize = 3
> >
> > gen dfsize1 = 0
> > replace dfsize1 = (1/8) if _n>3000
> >
> > gen p31 = (1/8)
> > replace p31 = (1/2) if _n<2001
> > replace p31 = (1/4) if (_n>2000 & _n<3001)
> >
> > gen p32 = 0
> > replace p32 = (1/8) if _n>3000
> >
> > save india31A.dta, replace
> >
> > ==================end=======================
> >
> >
> > ===============gender33A_lf.do=================
> > clear
> > set more 1
> >
> > capture program drop gender33A_lf
> > program gender33A_lf
> > version 8.2
> >
> > args lnf theta3 theta5
> >
> > tempvar q1 x1 x5
> >
> > quietly {
> > gen double `q1' = 1/(1+exp(`theta5'))
> >
> > gen double `x1' = 2^($ML_y1)
> >
> > gen double `x5' = norm(-`theta3')
> >
> > }
> > #delimit ;
> > quietly replace `lnf' = ln(($ML_y4*(1/`x1')*`x5') + ((1-
> `x5')*( $ML_y2*`q1' + $ML_y3*(1-`q1') )));
> > #delimit cr
> >
> > end
> >
> >
> > use india31A.dta /* Contains observations with N=2,3 */
> >
> >
> >
> > ml model lf gender33A_lf (dfsize p31 p32 dfsize1 = ) (),
> tech(bhhh nr)
> >
> > ml check
> >
> > ml search
> >
> > ml max, difficult
> >
> > =====================end=============================
> >
> >
> >
> > ==================output of gender33A_lf.do=================
> > . do gender33A_lf.do
> >
> > . clear
> >
> > . set more 1
> >
> > .
> > . capture program drop gender33A_lf
> >
> > . program gender33A_lf
> > 1. version 8.2
> > 2.
> > . args lnf theta3 theta5
> > 3.
> > . tempvar q1 x1 x5
> > 4.
> > . quietly {
> > 5. gen double `q1' = 1/(1+exp(`theta5'))
> > 6.
> > . gen double `x1' = 2^($ML_y1)
> > 7.
> > . gen double `x5' = norm(-`theta3')
> > 8.
> > . }
> > 9. #delimit ;
> > delimiter now ;
> > . quietly replace `lnf' = ln(($ML_y4*(1/`x1')*`x5') + ((1-
> `x5')*( $ML_y2*`q1' + $ML_y3*(1-`q1') )));
> > 10. #delimit cr
> > delimiter now cr
> > .
> > . end
> >
> > .
> > .
> > . use india31A.dta /* Contains observations with N=2,3 */
> >
> > .
> > .
> > .
> > . ml model lf gender33A_lf (dfsize p31 p32 dfsize1 = ) (),
> tech(bhhh nr)
> >
> > .
> > . ml check
> >
> > Test 1: Calling gender33A_lf to check if it computes log
> likelihood and
> > does not alter coefficient vector...
> > Passed.
> >
> > Test 2: Calling gender33A_lf again to check if the same log
> likelihood value
> > is returned...
> > Passed.
> >
> > Test 3: Calling gender33A_lf to check if 1st derivatives are
> computed...> test not relevant for method lf.
> >
> > Test 4: Calling gender33A_lf again to check if the same 1st
> derivatives are
> > returned...
> > test not relevant for method lf.
> >
> > Test 5: Calling gender33A_lf to check if 2nd derivatives are
> computed...> test not relevant for method lf.
> >
> > Test 6: Calling gender33A_lf again to check if the same 2nd
> derivatives are
> > returned...
> > test not relevant for method lf.
> >
> > ------------------------------------------------------------------
> ------------
> > Searching for alternate values for the coefficient vector to
> verify that
> > gender33A_lf returns different results when fed a different
> coefficient vector:
> >
> > Searching...
> > initial: log likelihood = -<inf> (could not be evaluated)
> > searching for feasible values +
> >
> > feasible: log likelihood = -9802.0949
> > improving initial values ..........
> > improve: log likelihood = -9802.0949
> >
> > continuing with tests...
> > ------------------------------------------------------------------
> ------------
> >
> > Test 7: Calling gender33A_lf to check log likelihood at the new
> values...> Passed.
> >
> > Test 8: Calling gender33A_lf requesting 1st derivatives at the
> new values...
> > test not relevant for method lf.
> >
> > Test 9: Calling gender33A_lf requesting 2nd derivatives at the
> new values...
> > test not relevant for method lf.
> >
> > ------------------------------------------------------------------
> ------------
> > gender33A_lf HAS PASSED ALL TESTS
> > ------------------------------------------------------------------
> ------------
> >
> > Test 10: Does gender33A_lf produce unanticipated output?
> > This is a minor issue. Stata has been running
> gender33A_lf with all
> > output suppressed. This time Stata will not suppress
> the output.
> > If you see any unanticipated output, you need to place
> quietly in
> > front of some of the commands in gender33A_lf.
> >
> > --------------------------------------------------------------
> begin execution
> > ----------------------------------------------------------------
> end execution
> >
> > .
> > . ml search
> > initial: log likelihood = -9802.0949
> > improve: log likelihood = -9802.0949
> > rescale: log likelihood = -9067.4074
> > rescale eq: log likelihood = -4852.0303
> >
> > .
> > . ml max, difficult
> >
> > initial: log likelihood = -4852.0303
> > rescale: log likelihood = -4852.0303
> > rescale eq: log likelihood = -4852.0303
> > (setting optimization to BHHH)
> > numerical derivatives are approximate
> > flat or discontinuous region encountered
> > numerical derivatives are approximate
> > flat or discontinuous region encountered
> > Iteration 0: log likelihood = -4852.0303
> > numerical derivatives are approximate
> > flat or discontinuous region encountered
> > numerical derivatives are approximate
> > flat or discontinuous region encountered
> > Iteration 1: log likelihood = -4852.0303 (backed up)
> > could not calculate numerical derivatives
> > missing values encountered
> > r(430);
> >
> > end of do-file
> > r(430);
> >
> > .
> > ====================end===========================
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
>
> --
> Stas Kolenikov
> http://stas.kolenikov.name
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
>
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
