Yes, was wondering that other code line did not change so much :-)
Thanks a lot!
2009/11/30 Gabor Grothendieck :
>
>
> On Sun, Nov 29, 2009 at 9:16 AM, Gabor Grothendieck
> wrote:
>>
>> By the way, if you really do want to create the formula anyways then:
>>
>> ix <- 1:2
>> left <- paste(n
On Sun, Nov 29, 2009 at 9:16 AM, Gabor Grothendieck wrote:
> By the way, if you really do want to create the formula anyways then:
>
>ix <- 1:2
>left <- paste(names(freeny)[ix], collapse = ",")
>fo <- as.formula(paste("cbind(", left, ") ~ ."))
>lm(fo, freeny)
>
> or possibly repla
By the way, if you really do want to create the formula anyways then:
ix <- 1:2
left <- paste(names(freeny)[ix], collapse = ",")
fo <- as.formula(paste("cbind(", left, ") ~ ."))
lm(fo, freeny)
or possibly replace last line with:
eval(substitute(lm(fo, freeny))
which will cause th
Gabor Grothendieck a écrit :
Try this:
ix <- 1:2
lm(as.matrix(freeny[ix]) ~., freeny[-ix])
clean and clever!!! Thanks a lot!! You really simplified the code!!!
Just for curiosity, do you see why parse(eval)) was not working twice in
same formula?
thanks a lot!!
Matthieu
On Sun, Nov 29,
Try this:
ix <- 1:2
lm(as.matrix(freeny[ix]) ~., freeny[-ix])
On Sun, Nov 29, 2009 at 8:56 AM, Matthieu Stigler <
matthieu.stig...@gmail.com> wrote:
> Thanks for answering so fast!!
>
>>
>> lm(freeny)
>>
> :-)
> Ok that's working for the one equation case :-) Was example case...
>
> But now I
Thanks for answering so fast!!
lm(freeny)
:-)
Ok that's working for the one equation case :-) Was example case...
But now I want to have not only first column of freeny on the left but
both first? And I don't know their names a priori...
Thanks!
On Sun, Nov 29, 2009 at 8:49 AM, Matthie
Try this:
lm(freeny)
On Sun, Nov 29, 2009 at 8:49 AM, Matthieu Stigler <
matthieu.stig...@gmail.com> wrote:
> Hi
>
> My goal is to do a (multiple) regression, just knowing that my Y variables
> will be the say k first variables of a matrix/data frame. I thought I should
> do it with eval(pars
Hi
My goal is to do a (multiple) regression, just knowing that my Y
variables will be the say k first variables of a matrix/data frame. I
thought I should do it with eval(parse)) but encounter a strange problem.
See:
lm(y~.-y, data=freeny) #that's what I want to do in the one equation case
#P
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