I don't know about "smooth.spline", but the "fda" package
includes "deriv.fd". It also includes "eval.fd" and "predict.fd". If
you only want a first derivative, then differentiating a standard cubic
spline may be adequate. However, the first derivative of a cubic spline
is a quadratic spline, the second derivative is a linear spline, and the
third derivative is a step function. The "fda" package provides more
alternative basis sets than the standard cubic splines, and may give you
results more to your liking.
Hope this helps.
Spencer
p.s. Full disclosure: I'm the third author on the Springer "Use R!"
book on "Functional Data Analysis with R and Matlab". I was the R
expert on the team that produced that book. The lead author, Jim
Ramsay, invented "functional data analysis" as a generalization of
spline smoothing to (a) bases other than the standard cubic b-splines
and (b) penalty functions other than the standard integral of the square
of the second derivative.
On 2/24/2012 12:33 PM, Vassily Shvets wrote:
Hello,
I've noticed that SPLUS has a function for evaluating the derivative matrices
of splines.
I've also noticed that there's a function in R for evaluating matrices from
smooth.spline;
maybe someone knows if something has been written to evaluate matrices from
'smooth.basis'?
regards,
s
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Spencer Graves, PE, PhD
President and Chief Technology Officer
Structure Inspection and Monitoring, Inc.
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