Using the builtin BOD data set try this: predict(lm(demand ~., BOD), se.fit = TRUE)
On 10/17/06, Li Zhang <[EMAIL PROTECTED]> wrote: > > Y X Z > 42.0 7.0 33.0 > 33.0 4.0 41.0 > 75.0 16.0 7.0 > 28.0 3.0 49.0 > 91.0 21.0 5.0 > 55.0 8.0 31.0 > > > data<-read.table("d.txt",header=TRUE) > mod<-lm(data$Y~data$X+data$Z) > predict(mod) > 1 2 3 4 5 6 > 44.69961 34.22997 76.63735 29.32986 91.09000 48.01321 > > > In the lm, the predicted(fitted) Y_1_hat is 44.6991, > > is there a function to give me the variance of > y_1_hat? > > Neither "anova" nor "summary" gives this value. > > Thank You > > ______________________________________________ > R-help@stat.math.ethz.ch 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. > ______________________________________________ R-help@stat.math.ethz.ch 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.