Re: st: maximum likelihood

[Maarten buis <maartenbuis@yahoo.co.uk>]

It is hard to comment on such code without knowing what kind of model you want to estimate, but the one thing that looks odd is that in case of "i==0" you have "1-" part that happens outside the "ln()". The element
inside ln() is usually a probability, so a "1-" often happens when you
want the complement of that. In that case the "1-" part should happen
within the "ln()" part.

However, I can't help but feel you should be able to do all this wihtout
resorting to -ml-, but instead look at -mlogit- maybe in combination with
-constraint- or -clogit-.

-- Maarten

--------------------------
Maarten L. Buis
Institut fuer Soziologie
Universitaet Tuebingen
Wilhelmstrasse 36
72074 Tuebingen
Germany

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


--- On Tue, 13/4/10, Abhimanyu Arora <abhimanyu.arora@student.kuleuven.be> wrote:

> From: Abhimanyu Arora <abhimanyu.arora@student.kuleuven.be>
> Subject: st: maximum likelihood
> To: statalist@hsphsun2.harvard.edu
> Date: Tuesday, 13 April, 2010, 12:06
> Dear statalist
> I have been trying to find the maximum likelihood estimates
> of my model, but
> I do not obtain standard errors (likelihood function
> non-concave and just a
> couple of iterations achieved). Following the section
> "Importance of
> generating temporary variables as doubles" pg 58-60 of the
> book by Gould et
> al, I generate temporary variables which are functions of
> my parameters to
> be estimated, only to obtain totally different coefficient
> values but still
> no standard errors+no concavity. What is the reason behind
> this puzzling
> phenomenon and its solution? Is my ml model command ok even
> though I may not
> have any _dependent_ variable as such?
> 
> Please find below the initial and final likelihood
> evaluators. I have two
> variables "i" (0/1) and "age"(1-5) and a constant matrix
> V(1X5) and need to
> find parameters theta_1 and R which determine the
> likelihood of each
> observation as below.  
> 
> Thanks and regards
> Abhimanyu Arora
> KU Leuven
> 
> 
> *******************
> Initial ml commands
> *******************
> 
> cap program drop maxl
> 
> program define maxl
> qui{
> args lnf theta_1 R
> 
> replace
> `lnf'=ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,2])+exp(`R'+0.9*V
> [1,1])) if i==1 & age ==1 
> 
> replace
> `lnf'=ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,3])+exp(`R'+0.9*V
> [1,1])) if i==1 & age ==2 
> 
> replace
> `lnf'=ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,4])+exp(`R'+0.9*V
> [1,1])) if i==1 & age ==3 
> 
> replace
> `lnf'=ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,5])+exp(`R'+0.9*V
> [1,1])) if i==1 & age ==4 
> 
> replace
> `lnf'=ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,5])+exp(`R'+0.9*V
> [1,1])) if i==1 & age ==5 
> 
> 
> replace
> `lnf'=1-ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,2])+exp(`R'+0.9
> *V[1,1])) if i==0 & age ==1
> replace
> `lnf'=1-ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,3])+exp(`R'+0.9
> *V[1,1])) if i==0 & age ==2
> replace
> `lnf'=1-ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,4])+exp(`R'+0.9
> *V[1,1])) if i==0 & age ==3
> replace
> `lnf'=1-ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,5])+exp(`R'+0.9
> *V[1,1])) if i==0 & age ==4
> replace
> `lnf'=1-ln((exp(`R'+0.9*V[1,1]))/exp(age*(`theta_1')+0.9*V[1,5])+exp(`R'+0.9
> *V[1,1])) if i==0 & age ==5
> 
> }
> 
> end
> ml model lf maxl (theta_1:) (R:)
> ml check
> ml init 0 0,copy
> ml maximize,difficult
> 
> *****************************************
> Introducing double temporary variables
> *****************************************
> cap program drop maxl
> 
> program define maxl
> qui{
> args lnf theta_1 R
> tempvar a b 
> gen double `a' =age*(`theta_1')
> gen double `b'=exp(`R'+0.9*V[1,1])
> 
> replace `lnf'=ln(`b'/(exp(`a'+0.9*V[1,2])+`b'))  if
> i==1 & age ==1 
> 
> replace `lnf'=ln(`b'/(exp(`a'+0.9*V[1,3])+`b'))  if
> i==1 & age ==2 
> 
> replace `lnf'=ln(`b'/(exp(`a'+0.9*V[1,4])+`b'))  if
> i==1 & age ==3 
> 
> replace `lnf'=ln(`b'/(exp(`a'+0.9*V[1,5])+`b'))  if
> i==1 & age ==4 
> 
> replace `lnf'=ln(`b'/(exp(`a'+0.9*V[1,5])+`b'))  if
> i==1 & age ==5 
> 
> 
> replace `lnf'=1-ln(`b'/(exp(`a'+0.9*V[1,2])+`b'))  if
> i==0 & age ==1
> replace `lnf'=1-ln(`b'/(exp(`a'+0.9*V[1,3])+`b'))  if
> i==0 & age ==2
> replace `lnf'=1-ln(`b'/(exp(`a'+0.9*V[1,4])+`b'))  if
> i==0 & age ==3
> replace `lnf'=1-ln(`b'/(exp(`a'+0.9*V[1,5])+`b'))  if
> i==0 & age ==4
> replace `lnf'=1-ln(`b'/(exp(`a'+0.9*V[1,5])+`b'))  if
> i==0 & age ==5
> 
> }
> 
> end
> ml model lf maxl (theta_1:) (R:)
> ml check
> ml init 0 0,copy
> ml maximize,difficult
> 
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