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

[peter dalgaard]

On May 14, 2012, at 02:24 , Luna wrote:

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


If correctly generalized, yes....

(Apologies for being slightly facetious; the point is that the properties you build on are part of the software design for model formulas and model matrices. They are not fortuitous buglets, so they are not going to go away unless the actual design is changed.)

> 
> 
> 
> 
> 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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-- 
Peter Dalgaard, Professor
Center for Statistics, Copenhagen Business School
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