I think you can estimate it using "gllamm". Take a look at the manuals
anna
----- Original Message -----
From: "Gang Peng" <[email protected]>
To: <[email protected]>
Sent: Tuesday, January 27, 2004 4:36 AM
Subject: Re: st: how to estimate mixed logit in Stata?
> Thanks Scott. I know that paper, but wondered if they have implemented the
> procedure in Stata. It seems not yet.
>
> ----- Original Message -----
> From: "Scott Merryman" <[email protected]>
> To: <[email protected]>
> Sent: Monday, January 26, 2004 7:33 PM
> Subject: Re: st: how to estimate mixed logit in Stata?
>
>
> > Kenneth Train at Berkeley has some Gauss programs to estimate mixed
logit
> models
> > (also called Random Parameters Logit and Error-Components Logit) using
> simulated
> > maximum likelihood.
> >
> > In a recent paper on mixed logit models (K. Train, "Halton Sequences for
> Mixed
> > Logit." ) he describes the mixed logit as follows:
> >
> > "A mixed logit (MXL) model is essentially a standard logit model with
> > coefficients that vary in the population. The routine estimates the
> distribution
> > of coefficients. MXL does not exhibit independence from irrelevant
> alternatives
> > as does standard logit, and allows correlation in unobserved utility
over
> > alternatives and over time.
> >
> > The utility of an alternative is specified as U=b'x+e, where x is a
vector
> of
> > observed variables (which vary over alternatives and agents), b is a
> vector of
> > unobserved coefficients that vary over agents but not over alternatives
> > (representing the agent's tastes), and e is an unobserved scalar
> distributed
> > extreme value iid over agents and alternatives.
> >
> > Each coefficient can take any of the following five distributions: (1)
> Fixed
> > coefficient: the coefficient is the same for all agents (i.e., a
> degenerate
> > distribution). (2) Normally distributed coefficient, with the mean and
> standard
> > deviation being estimated. (3) Uniformly distributed coefficients, with
> the mean
> > and "spread" being estimated. A uniform distribution with mean b and
> spread s
> > has a uniform density between b-s and b+s. (4) Triangularly distributed
> > coefficients, with the mean and "spread" being estimated. A triangular
> > distribution with mean b and spread s has zero density below b-s, rises
> linearly
> > from b-s to b, decreases linearly from b to b+s, and then is zero again
> above
> > b+s. (5) Log-normally distributed coefficient; the coefficient is
> calculated as
> > exp(c + s*u) where u is a standard normal deviate and c and s are
> parameters.
> > The program estimates c and s. The log-normal distribution with
parameters
> c and
> > s has median exp(c), mean m=exp[c+((s-squared)/2)], and standard
deviation
> > m*square-root of (exp(s-squared) - 1). "
> >
> > Scott
> >
> >
> >
> > ----- Original Message -----
> > >
> > > Gang Peng wrote:
> > >
> > > Are there any command for mixed logit model or do we have to write
code
> on
> > > our own? Any help? Comment?
> > >
> > >
> > >
> >
> > *
> > * For searches and help try:
> > * http://www.stata.com/support/faqs/res/findit.html
> > * http://www.stata.com/support/statalist/faq
> > * http://www.ats.ucla.edu/stat/stata/
> >
>
> *
> * For searches and help try:
> * http://www.stata.com/support/faqs/res/findit.html
> * http://www.stata.com/support/statalist/faq
> * http://www.ats.ucla.edu/stat/stata/
*
* For searches and help try:
* http://www.stata.com/support/faqs/res/findit.html
* http://www.stata.com/support/statalist/faq
* http://www.ats.ucla.edu/stat/stata/
