Re: Probit function

On Mon, 31 Aug 2009, Noah Silverman wrote:

> Thanks Achim,
>
> I discovered the Journal article just after posting this question.  It did 
> help explain more.
>
> My original inspiration for looking at this package came from a seminar 
> "summary" given in 2002.  Unfortunately , I can not find any actual published 
> paper or lecture notes that explain the lecturer's application of the MNP.
>
> Here is a link to the PDF of the summary: 
> http://www-stat.stanford.edu/seminars/stat/abstracts2001-2002/gu.pdf
>
> Most of the other published research on using logit or probit models for 
> horseracing data use a binary label of win/lose.  So, my thought was that 
> they were using the same for this application.
>
> Any thoughts?

As I said in my last mail: *Multi*nomial probit typically conveys more 
than 2 choices while *bi*nomial probit conveys exactly 2 choices.
Z

> --
> Noah
>
>
> On 8/31/09 5:07 PM, Achim Zeileis wrote:
>> On Mon, 31 Aug 2009, Noah Silverman wrote:
>> 
>>> Hello,
>>> 
>>> I want to start testing using the MNP probit function in stead of the lrm 
>>> function in my current experiment.
>>> 
>>> I have one dependant label and two independent varaibles.
>>> 
>>> The lrm is simple
>>> 
>>> model <- lrm(label ~ val1 + val2)
>>> 
>>> I tried the same thing with the mnp function and got an error that I don't 
>>> understand
>>> 
>>> model <- mnp(label ~ val1 + val2)
>>> 
>>> I get back an immediate error that tells me, "The number of alternatives 
>>> should be at least 3"
>>> 
>>> Since I have a binary training label, this looks like a problem. 
>>> (Additionally, I thought that a probit was a appropriate tool for building 
>>> binary models.)
>>> 
>>> Any advice?
>> 
>> *Multi*nomial probit typically conveys more than 2 choices while *bi*nomial 
>> probit conveys exactly 2 choices. One could argue that the latter should be 
>> a special case of the former but the more general case has much more 
>> computational challenges.
>> 
>> The =2 vs >2 information might have been inferred from the title of the 
>> package already but if you wanted to take extreme actions you could read 
>> the mnp() manual page or oven the references it points you to: The software 
>> is discussed in the Journal of Statistical Software 
>> (http://www.jstatsoft.org/v14/i03/) and the theory is described in an 
>> article in the Journal of Econometrics (124, 311-334).
>> 
>> Z
>> 
>>> Thanks!
>>> 
>>> -N
>>> 
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>