RE: st: problem 0 likelihood ml

[Olivier Francois <ofrancois@arec.umd.edu>]

Nick, Maarten,

Thank you very much for clarifying that.
Apologies for not spotting this problem, even though I have struggled with if before. 

The probit now works, but I still have the problem if I list more than one technique. 

The code has become the following:

//creating the data
clear
set more off
set seed 12345
set obs 1000
matrix C = I(4)
drawnorm z v e x, corr(C)
replace z = sqrt(2)*z
scalar a0 = 2
scalar a1 = -1
gen D = (a0 + a1*z > v)
gen Y = 0.5 - 0.5*x + e

//Probit model
apture program drop myprobit
program myprobit
    version 11.2
    args lnf xgam

    quietly {
        replace `lnf' = ln(normal(-`xgam')) if $ML_y1 == 0
        replace `lnf' = ln(normal(`xgam')) if $ML_y1 == 1
    }
end

ml model lf myprobit (xgam: D = z), vce(robust) technique(nr bhhh)
ml check

/*It works fine with just one technique (any), but come back with the following error if I combine more than one technique:
       opt__eval_cycle():  3301  subscript invalid
            opt__eval():     -  function returned error
    _optimize_evaluate():     -  function returned error
       _mopt__evaluate():     -  function returned error
     mopt__check_test1():     -  function returned error
      _moptimize_check():     -  function returned error
            Mopt_check():     -  function returned error
                 <istmt>:     -  function returned error
*/



________________________________________
From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Maarten Buis [maartenlbuis@gmail.com]
Sent: Friday, November 16, 2012 10:08 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: problem 0 likelihood ml

On Fri, Nov 16, 2012 at 3:45 PM, Olivier Francois wrote:
> I needed to create my own likelihood function and have been running into problems. I have been trying to use program and the ml commands, but there is something I must not do correctly.
<snip>
>     if $ML_y1 == 0 {
>         replace `lnf' = ln(normal(-`xgam'))
>     }
>
>     else if $ML_y1 == 1 {
>             replace `lnf' = ln(normal(`xgam'))
>     }

The way you have used -if- means that it takes a scalar, in this case
the first observation of the dependent variable, and checks whether it
is 0 or 1, and applies the likelihood computation for all observations
based on that test, compare -help if- with -help ifcmd-. What you want
is to tell Stata to check for each observation whether the dependent
variable is 0 or 1 and choose the appropriate log likelihood function
accordingly. You can do that as folows:

replace `lnf' = ln(normal(-`xgam')) if $ML_y1 == 0
replace `lnf' = ln(normal( `xgam')) if $ML_y1 == 1

alternatively:

replace `lnf' = $ML_y1*ln(normal(`xgam') + (1-$ML_y1)*ln(normal(-`xgam'))

The latter will allow you to estimate a probit and a fractional probit.

Hope this helps,
Maarten

---------------------------------
Maarten L. Buis
WZB
Reichpietschufer 50
10785 Berlin
Germany

http://www.maartenbuis.nl
---------------------------------
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