[R] Probit function
Achim Zeileis
Achim.Zeileis at wu-wien.ac.at
Tue Sep 1 04:17:42 CEST 2009
On Mon, 31 Aug 2009, Noah Silverman wrote:
> Um..... I did my research. Have been for years. I assume you're referring
> to Boltman and Chapmanm "A multinomial logit model for handicapping horse
> races" included in "Efficiency of racetrack betting markets". Page 155
> references what they call a "multinomial model". From equation 14 in their
> paper, it appears as if they are calculating "Utility" of a horse as a
> number. Far from what I understand a traditional "Multinomial" model is.
>
> The seminar that I referenced discussed using a probit model instead of a
> logit model. Since the Boltman and Chapman application didn't really have
> multiple discreet choices, I'm not sure how the probit model would. Hence my
> inquiry.
But of course it has multiple choices (finishing ranks instead of binary
win/lose), otherwise it wouldn't be very multinomial, would it?
Z
>
>
> On 8/31/09 6:23 PM, Achim Zeileis wrote:
>> 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
>>>>>>>
>>>>>>> ______________________________________________
>>>>>>> R-help at r-project.org mailing list
>>>>>>> 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.
>>>>>>>
>>>>>>>
>>>>>
>>>
>
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