Dear all, I would like to fit a linear regression with replication (on each year, observation is replicated, e.g 4 times). The independent variable ranges for instance 1-5 year, so I expect to have a linear fit of 5 points. For that purpose I do these (with dummy variables x and y):
x<-rep(seq(1:5),4) y<-rnorm(20) linreg<-lm(y~x) fitted.values(linreg) # why produce 20 points of estimate? predict(linreg) # why produce 20 points of estimate? Please somebody explain: 1. why both fitted.values and predict functions produced 20 points of estimate, NOT 5 points. 2. is "lm(y~x)" correct to solve this regression case, or there's a correct procedure. Many thanks. ______________________________________________ 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.
