PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html and provide commented,
minimal, self-contained, reproducible code.
I do NOT know how to do what you want, but with a self-contained
example, I suspect many people on this list -- probably including me --
could easily solve the problem. Without such an example, there is a
high probability that any answer might (a) not respond to your need, and
(b) take more time to develop, just because we don't know enough of what
you are asking.
Spencer
[EMAIL PROTECTED] wrote:
Like I indicated. I understand the coefficients in a B-spline context. If I use
the the 'spline' or 'splinefun' I can get the coefficients and they are grouped
as 'a', 'b', 'c', and 'd' coefficients. But the coefficients for smooth.spline
is just an array. I basically want to take these coefficients and outside of
'R' use them to form an interpolation. In other words I want 'R' to do the hard
work and then export the results so they can be used else where.
Thank you.
Kevin
Spencer Graves wrote:
I believe that a short answer to your question is that the
"smooth" is a linear combination of B-spline basis functions, and the
coefficients are the weights assigned to the different B-splines in
that basis.
Before offering a much longer answer, I would want to know what
problem you are trying to solve and why you want to know. For a brief
description of B-splines, see
"http://en.wikipedia.org/wiki/B-spline";. For a slightly longer
commentary on them I suggest the "scripts\ch01.R" in the DierckxSpline
package: That script computes and displays some B-splines using
"splineDesign", "spline.des" in the 'splines' package plus comparable
functions in the 'fda' package. For more info on this, I found the
first chapter of Paul Dierckx (1993) Curve and Surface Fitting with
Splines (Oxford U. Pr.). Beyond that, I've learned a lot from the
'fda' package and the two companion volumes by Ramsay and Silverman
(2006) Functional Data Analysis, 2nd ed. and (2002) Applied Functional
Data Analysis (both Springer).
If you'd like more help from this listserve, PLEASE do read the
posting guide http://www.R-project.org/posting-guide.html and provide
commented, minimal, self-contained, reproducible code.
Hope this helps. Spencer Graves
[EMAIL PROTECTED] wrote:
I like what smooth.spline does but I am unclear on the output. I can
see from the documentation that there are fit.coef but I am unclear
what those coeficients are applied to.With spline I understand the
"noraml" coefficients applied to a cubic polynomial. But these
coefficients I am not sure how to interpret. If I had a description
of the algorithm maybe I could figure it out but as it is I have this
question. Any help?
Kevin
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