Why can we combine design matrix and data-frame in R?

Thanks!

Do you think if the correctness of the such results could be generalized to
other future cases?

On Sun, May 13, 2012 at 7:10 PM, S Ellison <S.Ellison at lgcgroup.com> wrote:

But the line you cited was about "response" being a matrix, which is not

our case.
Yes, you're right; I picked the wrong thing to cite.
The only documentation I found about lm accepting a matrix in the
predictors is a one-line statement in "Introduction to R" which says "term_i
  is either

      a vector or matrix expression, or 1,
      a factor, or
      a formula expression consisting of factors, vectors or matrices
connected by formula operators. "

Not the most informative documentation. But Peter Dalgaard is a most
authoritative source!

And also I have checked:

Any more thoughts?

Data frames are odd things; a column need not contain only a vector if the
number of rows is OK. I am half surprised that including a matrix in one
works. But the gods of R are powerful and their magic is strong. Here,
names(tmp) is showing that the data frame has one element called X (in
effect, the whole matrix is regarded as one element of the data frame), but
on display the magic has expanded X to show all the columns of X.

This is the main reason I generally keep to simple things in data frames;
complicated things make it less easy to predict behaviour.



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