# st: nl in which the nonlinear functional form is conditional on x

 From Quang Nguyen To statalist@hsphsun2.harvard.edu Subject st: nl in which the nonlinear functional form is conditional on x Date Tue, 14 Apr 2009 09:19:53 -1000

```Dear All:

I have the model as follows: y = F(x;  lamda) for x>0 and y= G(x:
lamda) for x<0. Both F and G are nonlinear. Do you think we can use
_nl_ to estimate this model? Is there a way we can write like this:

nl {( y = F(x;  lamda) if  x>0 ) (y= G(x: lamda) if x<0)}

Many thanks!

On Tue, Apr 14, 2009 at 6:54 AM, Martin Weiss <martin.weiss1@gmx.de> wrote:
> <>
>
> Rudy may also want to take a cue from the MUS book datasets at
> http://www.stata-press.com/data/mus.html
> File mus04p1sim.do shows how the pros use -simulate- with the -seed- set...
>
>
> HTH
> Martin
> _______________________
> ----- Original Message ----- From: "Eva Poen" <eva.poen@gmail.com>
> To: <statalist@hsphsun2.harvard.edu>
> Sent: Tuesday, April 14, 2009 6:10 PM
> Subject: Re: st: question about monte carlo study
>
>
>> <>
>>
>> I don't think this is a good idea. Setting the random seed inside the
>> simulation program leads to the same random numbers being drawn at
>> every replication.
>>
>>
>> program olssim
>> ...
>> end
>>
>> set seed 123
>> simulate ...
>>
>>
>> Eva
>>
>>
>> 2009/4/14 Joao Ricardo F. Lima <jricardofl@gmail.com>:
>>>
>>> Rudy,
>>>
>>> another option:
>>>
>>> capture program drop olssim
>>> program olssim
>>> version 10.0
>>> drop _all
>>> set obs 100
>>> set seed 123
>>> generate e = invnorm(uniform())*2
>>> generate x = uniform()*10
>>> generate y = 1 + 0.5 * x + e
>>> regress y x
>>> end
>>> simulate, reps(1000) : olssim
>>>
>>> HTH,
>>>
>>> Joao Lima
>>>
>>> 2009/4/14 Rudy Fichtenbaum <rudy.fichtenbaum@wright.edu>:
>>>>
>>>> I am running a monte carlo simulation using the following program:
>>>>
>>>> capture program drop olssim
>>>> program olssim, rclass
>>>> version 10.0
>>>> drop _all
>>>> set obs 100
>>>> generate e = invnorm(uniform())*2
>>>> generate x = uniform()*10
>>>> generate y = 1 + 0.5 * x + e
>>>> regress y x
>>>> return scalar b0 = _coef[_cons]
>>>> return scalar b1 = _coef[x]
>>>> end
>>>>
>>>> simulate "olssim" b0 = r(b0) b1 = r(b1), reps(1000)
>>>>
>>>> sum b0 b1, detail
>>>>
>>>> The problem I am having is that each time I run the program I get a
>>>> slightly
>>>> different result. I know this is because I have not set the seed for the
>>>> random number generator but I can't figure out how to set the seed in
>>>> this
>>>> program.
>>>>
>>>> Rudy
>>>>
>>>> --
>>>> Rudy Fichtenbaum
>>>> Professor of Economics
>>>> Chief Negotiator AAUP-WSU
>>>> Wright State University
>>>> Dayton, OH 45435-0001
>>>> 937-775-3085
>>>>
>>>> *
>>>> * For searches and help try:
>>>> * http://www.stata.com/help.cgi?search
>>>> * http://www.stata.com/support/statalist/faq
>>>> * http://www.ats.ucla.edu/stat/stata/
>>>>
>>>
>>>
>>>
>>> --
>>> ----------------------------------------
>>> Joao Ricardo Lima, D.Sc.
>>> Professor
>>> UFPB-CCA-DCFS
>>> Fone: +5538387264913
>>> Skype: joao_ricardo_lima
>>> ----------------------------------------
>>>
>>> *
>>> * For searches and help try:
>>> * http://www.stata.com/help.cgi?search
>>> * http://www.stata.com/support/statalist/faq
>>> * http://www.ats.ucla.edu/stat/stata/
>>>
>>
>> *
>> *   For searches and help try:
>> *   http://www.stata.com/help.cgi?search
>> *   http://www.stata.com/support/statalist/faq
>> *   http://www.ats.ucla.edu/stat/stata/
>>
>
> *
> *   For searches and help try:
> *   http://www.stata.com/help.cgi?search
> *   http://www.stata.com/support/statalist/faq
> *   http://www.ats.ucla.edu/stat/stata/
>

--
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he believed in me." - Jim Valvano

*
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```