Sven Garbade <[EMAIL PROTECTED]> writes: > Hi all, > > suppose I've got a vector y with some data (from a repeated measure > design) observed given the conditions in f1 and f2. I've got a model > with two unknown fix constants a and b which tries to predict y with > respect to the values in f1 and f2. Here is an exsample > > # "data" > y <- c(runif(10, -1,0), runif(10,0,1)) > # f1 > f1 <- rep(c(-1.4, 1.4), rep(10,2)) > # f2 > f2 <- rep(c(-.5, .5), rep(10,2)) > > Suppose my simple model looks like > > y = a/f1 + b*f2 > > Is there a function in R which can compute the estimates for a and b? > And is it possible to test the model, eg how "good" the fits of the > model are?
f2 and 1/f1 are exactly collinear, so no, not in R, nor any other way. Apart from that, the model is linear in a and b so lm() can fit it (with different f1 and f2) if you're not too squeamish about the error distribution. -- O__ ---- Peter Dalgaard Blegdamsvej 3 c/ /'_ --- Dept. of Biostatistics 2200 Cph. N (*) \(*) -- University of Copenhagen Denmark Ph: (+45) 35327918 ~~~~~~~~~~ - ([EMAIL PROTECTED]) FAX: (+45) 35327907 ______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
