[R] Probit function

[Achim Zeileis]

On Mon, 31 Aug 2009, Noah Silverman wrote:

> I get that.
>
> Still trying to figure out what the "multi" nominal labels they used were. 
> That's why I passed on the reference to the seminar summary.

So that I could do the research for you? Come on...the usual strategy 
applies: Look at the references! (Hint: The information is in the Bolton 
and Chapman paper.)
Z

>
> On 8/31/09 5:40 PM, Achim Zeileis wrote:
>> 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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>>>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>>>> PLEASE do read the posting guide 
>>>>> http://www.R-project.org/posting-guide.html
>>>>> and provide commented, minimal, self-contained, reproducible code.
>>>>> 
>>>>> 
>>> 
>