Hi, this question is probably very obvious but I just cant see where I might be going wrong.
I'm using the lm() function to generate a linear model and then make predictions using a different set of data. To generate the model I do (tdata & pdata are matrices of observations and parameters, tdepv, pdepv are response vectors) x <- as.data.frame(tdata) x$tdepv <- tdepv lnegth(tdepv) = 140 model <- lm(x$tdepv ~ x$V1 + x$V2 + x$V3 + x$V4, x) pred <- predict(model, x) length(pred) = 140 y <- as.data.frame(pdata) y$pdepv <- pdepv length(pdepv) = 16 pred <- predict(model, y) length(pred) = 140 But I expect that length(pred) = 16 Why do I get a different length? Furthermore, the original formula specified the variable tdepv which is not in the dataframe that I send to predict() - should I also make a variable called tdepv in the dataframe y? Thanks, ------------------------------------------------------------------- Rajarshi Guha <[EMAIL PROTECTED]> <http://jijo.cjb.net> GPG Fingerprint: 0CCA 8EE2 2EEB 25E2 AB04 06F7 1BB9 E634 9B87 56EE ------------------------------------------------------------------- The way to love anything is to realize that it might be lost. ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
