
From  "Gauri Khanna" <gwkhanna@hotmail.com> 
To  statalist@hsphsun2.harvard.edu 
Subject  RE: st: ML estimation, no feasible valuesGauri, 6th July 
Date  Fri, 07 Jul 2006 13:26:24 +0000 
Thank you Maarten, I will try what you suggest. Gauri
From: "Maarten Buis" <M.Buis@fsw.vu.nl>_________________________________________________________________
ReplyTo: statalist@hsphsun2.harvard.edu
To: <statalist@hsphsun2.harvard.edu>
Subject: RE: st: ML estimation, no feasible valuesGauri, 6th July
Date: Fri, 7 Jul 2006 12:00:16 +0200
Your likelihood function is the likelihood function of a probit
model. This would explain why your program isn't working, you
only get values of the likelihood functions if your dependent
variable/explained variable/y is either exactly 1 or 0, for all
other cases with other values of y no likelihood is calculated.
There are easier ways to get the log likelihood after a
regress statement than build your own ml program: After you
estimated the OLS model with regress, the log likelihood is
stored in e(ll), so type display e(ll) will display the log
likelihood. If you really want to iterate (which is not
necessary for the maximum likelihood of a normal model, hence
why regress could return the likelihood without iterating)
you can use glm: glm outputpsp corareapsp labourpsp
manurepsp fertiliserpsp tracpsp oxpsp irripsp, family(normal)
link(identity)
HTH,
Maarten

Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands
visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z214
+31 20 5986715
http://home.fsw.vu.nl/m.buis/

Original Message
From: ownerstatalist@hsphsun2.harvard.edu [mailto:ownerstatalist@hsphsun2.harvard.edu]On Behalf Of Gauri Khanna
Sent: vrijdag 7 juli 2006 9:17
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: ML estimation, no feasible valuesGauri, 6th July
Dear Rodrigo,
Thank you for your reply.
I am not estimating a Probit model. My dependant variable is continuos. I
had used my equation to run an ordinarly OLS using the regress command such
as below.
regress outputpsp corareapsp labourpsp manurepsp fertiliserpsp tracpsp oxpsp
irripsp
Now I would like to estimate the loglikelihood value for this same model
above using the ML method.
I refered to the term loglinear because all my variables are in log form and
are linear.
Any ideas?
Thanks,
Gauri
>From: "Rodrigo A. Alfaro" <ralfaro76@hotmail.com>
>ReplyTo: statalist@hsphsun2.harvard.edu
>To: <statalist@hsphsun2.harvard.edu>
>Subject: Re: st: ML estimation, no feasible valuesGauri, 6th July
>Date: Thu, 6 Jul 2006 17:52:00 0400
>
>Dear Gauri,
>
>Your program (mylog) solves a probit model. Is this what
>you want? I don't understand what loglinear means for you.
>If the answer is yes, I assume that your dependent variable
>is 0 or 1 and I suggest to use probit instead.
>
>Otherwise, check glm command take a loof of options
>family() and link() maybe gaussian and log is what you need
>Or provide the model that you want to estimate.
>
>Rodrigo.
>
>
> Original Message 
>From: "Deepankar Basu" <basu.15@osu.edu>
>To: <statalist@hsphsun2.harvard.edu>
>Sent: Thursday, July 06, 2006 4:37 PM
>Subject: Re: st: ML estimation, no feasible valuesGauri, 6th July
>
>
>I think the only think that is missing is another empty bracket for
>theta1 in your ml model command. Try the following:
>
>ml model lf mylog (outputpsp=corareapsp labourpsp manurepsp
>fertiliserpsp tracpsp oxpsp irripsp) ()
>
>Nothing else needs to be changed.
>HTH,
>Deepankar
>
>On Thu, 20060706 at 20:18 +0000, Gauri Khanna wrote:
> > Dear Statalist,
> >
> > I am trying to run an ml maximisation to calculate loglikehood values
>for
> > my
> > model which has only one equation. It is a loglinear equation.
> > unfortunately
> > I run into problems as no feasible values are found, error message
>r(491).
> > I
> > even tried the ml search, repeat(10) and also with ml maximize,difficult
> > and
> > also with ml maximize, ltol(1e4) but I got the same error message
>r(491)
> > that I have pasted below. I only want to obtain the loglikelihood value
> > estimated, nothing else!
> >
> > MY COMMANDS:
> >
> > capture program drop mylog
> > program mylog
> > version 8
> > args lnf theta1
> > quietly replace `lnf' = ln(norm(`theta1')) if $ML_y1==1
> > quietly replace `lnf' = ln(norm(`theta1')) if $ML_y1==0
> > end
> >
> > ml model lf mylog (outputpsp=corareapsp labourpsp manurepsp
>fertiliserpsp
> > tracpsp oxpsp irripsp)
> > ml check
> > ml search
> > ml maximize
> >
> >
> > OUTPUT GENERATED IN STATA
> >
> > . capture program drop mylog
> >
> > . program mylog
> > 1. version 8
> > 2. args lnf theta1
> > 3. quietly replace `lnf' = ln(norm(`theta1')) if $ML_y1==1
> > 4. quietly replace `lnf' = ln(norm(`theta1')) if $ML_y1==0
> > 5. end
> >
> > .
> > . ml model lf mylog (outputpsp=corareapsp labourpsp manurepsp
> > fertiliserpsp
> > tracpsp oxpsp
> > > irripsp)
> >
> > . ml check
> >
> > Test 1: Calling mylog to check if it computes log likelihood and
> > does not alter coefficient vector...
> > Passed.
> >
> > Test 2: Calling mylog again to check if the same log likelihood value
> > is returned...
> > Passed.
> >
> >
>
> > The initial values are not feasible. This may be because the initial
> > values
> > have been chosen poorly or because there is an error in mylog and it
> > always returns missing no matter what the parameter values.
> >
> > Stata is going to use ml search to find a feasible set of initial
>values.
> > If mylog is broken, this will not work and you will have to press Break
> > to make ml search stop.
> >
> > Searching...
> > initial: log likelihood = <inf> (could not be evaluated)
> > searching for feasible values
> > ...........................................................
> > >
> > ......................................................................
> > >
> >
>.......................................................................................
> > >
> >
>.......................................................................................
> >
> >...........................................................................
> >
> > could not find feasible values
> > r(491);
> >
> >
> > Please HELP, what can I do with my model "mylog" to make it find
>feasible
> > values?
> >
> > Thanking you in advance.
> >
> > Gauri
> >
> > _________________________________________________________________
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