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 > >> -- >> 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.
