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: >>> >>>> 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@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. >>>>>> >>>>>> >>>> >> [[alternative HTML version deleted]] ______________________________________________ R-help@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.
