[R] question about predictions with linear models

[Rajarshi Guha]

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,

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Rajarshi Guha <rxg218 at psu.edu> <http://jijo.cjb.net>
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