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Noah Silverman | 1 Sep 2009 02:16

Re: Probit function

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?

--
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.
>>
(Continue reading)

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Achim Zeileis | 1 Sep 2009 02:40
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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:
(Continue reading)

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Noah Silverman | 1 Sep 2009 02:52

Re: Probit function

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.

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
(Continue reading)

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Achim Zeileis | 1 Sep 2009 03:23
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Re: Probit function

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
(Continue reading)

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Noah Silverman | 1 Sep 2009 04:04

Re: Probit function

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.

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:
>>>
(Continue reading)

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Achim Zeileis | 1 Sep 2009 04:17
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Re: Probit function

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
(Continue reading)

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Noah Silverman | 1 Sep 2009 04:25

Re: Probit function

It is my understanding that they ARE using a binary model.  In fact, 
they even discuss "exploding" the model to count second and third place 
finishers as "winners".  Otherwise, how can one calculate the 
probability of the positive class (winner)?  If I'm mistaken and they 
are in fact predicting rank, would you please show me where that is in 
their paper.

Thanks!

-N

On 8/31/09 7:17 PM, Achim Zeileis wrote:
> 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
(Continue reading)

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