Help: lda predict
Thanks for your reply. Actually I called function as below. p1 = predict(object, newdata, dimen=1) p2 = predict(object, newdata, dimen=1, method=debiased) p3 = predict(object, newdata, dimen=1, method="predictive") The MAP classification of prediction results by any method are the same. I know what the method "plug-in" and "debiased" mean, but what does the "vague prior" for the method "predictive" mean? what is "vague" here? Thank you, Shengzhe
On 8/26/05, Prof Brian Ripley <ripley at stats.ox.ac.uk> wrote:
On Fri, 26 Aug 2005, Shengzhe Wu wrote:
I use lda (package: MASS) to obtain a lda object, then want to employ
this object to do the prediction for the new data like below:
predict(object, newdata, dimen=1, method=c("plug-in", "predictive", "debiased"))
That is not how you call it: when a character vector is given like that those are alternatives. Do read the help page, as we ask.
What is the exact difference among the three methods? What is the difference of prediction results when applying different method?
This is stated on the help page. If you are unfamiliar with the area, note that the posting guide points out that MASS is support software for a book and the explanations are in the book. The help page also has references: please do read them (before posting).
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
-- Brian D. Ripley, ripley at stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595