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# Re: st: RE: Using ml with hard-coded variables.

 From "Nick B." <3kdo02s@gmail.com> To statalist@hsphsun2.harvard.edu Subject Re: st: RE: Using ml with hard-coded variables. Date Thu, 17 May 2007 20:00:59 -0400

```I believe -norm()- functions as -normal()- (CDF), which I think is
what I want (the non-hard-coded version described below, which also
uses -norm()-, matches the "probit foreign mpg" result).

By the way, I've been looking at Nick Cox's example at
http://www.stata.com/statalist/archive/2006-03/msg01102.html as a
basis for ml estimation with only hard-coded variables, but although
that works fine, I can't figure out what I'm doing differently...

On 5/17/07, Nick Cox <n.j.cox@durham.ac.uk> wrote:
```
```-norm()- is not a synonym for -normalden()-.

The difference is between the cumulative distribution
function and the density function.

This may have some bearing on your problem.

Nick
n.j.cox@durham.ac.uk

P.S. Good name, but you may have to change it.

Nick B.

> I'm a beginner here, trying to use Stata's ml to estimate a
> probit-like equation with non-linear terms.  However, whenever I try
> using hard-coded independent variables, I get the following error:
>
> initial:       log likelihood = -51.292891
> alternative:   log likelihood =  -1877.398
> rescale:       log likelihood = -48.015768
> rescale eq:    log likelihood = -48.015768
> could not calculate numerical derivatives
> flat or discontinuous region encountered
>
> Even when I simplify my system, I still get these errors, so I must be
> doing something wrong.
>
> For instance, using the built-in auto data, I try
> -----
> sysuse auto
> capture program drop probit1
>
> program define probit1
>       args lnf theta1
>       tempvar p
>       quietly gen double `p'=norm(`theta1'*mpg)
>       quietly replace `lnf' = \$ML_y1*ln(`p')+(1-\$ML_y1)*ln(1-`p')
> end
>
> ml model lf probit1 (foreign=) /beta1
> ml max
> ------
> This produces the error, even though it is almost identical to the
> textbook example for using ml for probit.  Specifically, replacing the
> relevant lines with the non-hard-coded version
>
> quietly gen double `p'=norm(`theta1')
> ml model lf probit1 (foreign=mpg)
>
> works fine.  So I assume I am doing something basic wrong in switching
> to hard-coded variables.
>
>
> The reason I need the hard-coded variables is that what I'm really
> trying to estimate is closer to
> ----
> capture program drop probit2
>
> program define probit2
>       args lnf theta1 theta2 theta3 theta4
>       tempvar p
>       quietly gen double
> `p'=norm(((`theta1'*mpg)^`theta3'+(`theta2'*length)^`theta3')^
> `theta4')
>       quietly replace `lnf' = \$ML_y1*ln(`p')+(1-\$ML_y1)*ln(1-`p')
> end
>
> ml model lf probit2 (foreign=) /beta1 /beta2 /gamma1 /gamma2
>
> ml max
> ----
> Which of course produces the same error.
>
> Any help would be greatly appreciated.

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```
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```

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