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
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 "
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 th
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
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 reference
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 ju
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
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 thi
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 tha
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