You use the function "predict" for that. You give a data frame with the new observations, and make sure the variables have exactly the same name.
# run example library(MASS) Class <- as.factor(rep(c("A","B","C"),each=30)) X1 <- c(rnorm(30),rnorm(30,3,2),rnorm(30,-3,1)) X2 <- c(rnorm(30,5,3),rnorm(30,-2,4),rnorm(30,2,2)) result <- lda(Class~X1+X2) newdat <- data.frame(X1=rnorm(10),X2=rnorm(10,5,3)) predictions <- predict(result,newdat) # predictions$class # gives the class to which the new observation belongs predictions$posterior # gives the posterior probabilities for each observation and for all classes # end example Cheers Joris On Sat, Jun 5, 2010 at 6:37 AM, suman dhara <suman.dhar...@gmail.com> wrote: > Sir, > I am working with multiclass discriminant analysis.(say response variable > has 3classes).In R, using lda(), I get 2 sets of coefficients for the > discriminant function.Now, I want to put a new x-vector(vector of > independent variables) and want to check it corresponds to which class of > y.Is there any formula for doing this? or how can I do this? > > > > Regards, > Suman Dhara > > [[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. > -- Ghent University Faculty of Bioscience Engineering Department of Applied mathematics, biometrics and process control tel : +32 9 264 59 87 joris.m...@ugent.be ------------------------------- Disclaimer : http://helpdesk.ugent.be/e-maildisclaimer.php ______________________________________________ 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.