egree, raw = raw))
1: poly(m, degree = 6, raw = TRUE)
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -Original Message-
> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
> Behalf Of YTP
> Sent: Tuesday, July 10, 2012 11:23 AM
> To: r-help@r
Yep, that code is verbatim what I typed in, using version 2.14 ... seems
weird.
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Hello,
Em 08-07-2012 03:00, Peter Ehlers escreveu:
On 2012-07-07 14:56, YTP wrote:
Hi Rui,
Thanks for responding. I did not write "raw=raw", and I'm not sure why R
would return such a misleading error message. Indeed, the same error
message
comes up when I run the 2nd part of your code:
m <
On 2012-07-07 14:56, YTP wrote:
Hi Rui,
Thanks for responding. I did not write "raw=raw", and I'm not sure why R
would return such a misleading error message. Indeed, the same error message
comes up when I run the 2nd part of your code:
m <- matrix(1:6, ncol=2)
p6 <- poly(m, degree=6, raw=TRUE
Hi Rui,
Thanks for responding. I did not write "raw=raw", and I'm not sure why R
would return such a misleading error message. Indeed, the same error message
comes up when I run the 2nd part of your code:
> m <- matrix(1:6, ncol=2)
> p6 <- poly(m, degree=6, raw=TRUE)
Error in poly(dots[[1L]],
Hello,
Sorry, but it was you that misread some of the suggestions. I have
written raw=TRUE not raw=raw. Just see
m <- matrix(1:6, ncol=2) # your example
p2 <- poly(m, degree=2, raw=TRUE) # it's raw=TRUE, not raw=raw !!!
deg2 <- attr(p2, 'degree') == 2
p2[, deg2]
p6 <- poly(m, degree=6, raw
I think you have taken my toy example seriously. Perhaps I wasn't clear, but
I am in fact not working with a dataset of 3 observations of the numbers 1
through 6 and trying to estimate anything; that was an example to illustrate
what I am asking for, namely, turning two variables like this
X1 X2
On Jul 2, 2012, at 4:13 PM, YTP wrote:
I am not sure that method works. It appears to be doing something
close, but
returns too many slope coefficients, since I think it is returning
interaction terms of degree smaller and greater than what was passed
to it.
No. It _was_ doing what you as
I am not sure that method works. It appears to be doing something close, but
returns too many slope coefficients, since I think it is returning
interaction terms of degree smaller and greater than what was passed to it.
Here is a small example of degree 2:
> X = data.frame(cbind(c(1,2,3), c(4,5,
Hi Bert, thank you for pointing out that this method does not work. Do you
happen to have any ideas as to how it could be done? Many thanks.
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Sent fr
Hello,
Another way is to cbind the vectors 'a' and 'b', but this needs argument
'raw' set to TRUE.
poly(cbind(a, b), 6, raw=TRUE)
To the OP: is this time series related? With 6 being a lag or test
(e.g., Tsay, 1986) order? I'm asking this because package nlts has a
function for this test up
Inline below.
-- Bert
On Mon, Jul 2, 2012 at 8:04 AM, David Winsemius wrote:
>
> On Jul 2, 2012, at 10:51 AM, David Winsemius wrote:
>
>
>> On Jul 2, 2012, at 9:29 AM, YTP wrote:
>>
>> I would like to specify a model with all polynomial interaction terms
>>> between
>>> two variables, say, up t
On Jul 2, 2012, at 10:51 AM, David Winsemius wrote:
On Jul 2, 2012, at 9:29 AM, YTP wrote:
I would like to specify a model with all polynomial interaction
terms between
two variables, say, up to degree 6. For example, terms like a^6 +
(a^5 *
b^1) + (a^4 * b^2) + ... and so on. The doc
On Jul 2, 2012, at 9:29 AM, YTP wrote:
I would like to specify a model with all polynomial interaction
terms between
two variables, say, up to degree 6. For example, terms like a^6 +
(a^5 *
b^1) + (a^4 * b^2) + ... and so on. The documentation states
The ^ operator indicates crossing to
I would like to specify a model with all polynomial interaction terms between
two variables, say, up to degree 6. For example, terms like a^6 + (a^5 *
b^1) + (a^4 * b^2) + ... and so on. The documentation states
The ^ operator indicates crossing to the specified degree.
so I would expect a mod
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