[R] Taking the derivative of a quadratic B-spline

[Huntsinger, Reid]

The derivative of a quadratic B-spline is the centered finite difference of
a linear B-spline, so if you have access to the underlying coefficients of
the B-spline expansion you can do this easily. I believe the coefficients
are passed as the $coef component of the return value.

Reid Huntsinger

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of James McDermott
Sent: Tuesday, July 19, 2005 2:54 PM
To: r-help at stat.math.ethz.ch
Subject: [R] Taking the derivative of a quadratic B-spline


Hello,

I have been trying to take the derivative of a quadratic B-spline
obtained by using the COBS library.  What I would like to do is
similar to what one can do by using

fit<-smooth.spline(cdf)
xx<-seq(-10,10,.1)
predict(fit, xx, deriv = 1)

The goal is to fit the spline to data that is approximating a
cumulative distribution function (e.g. in my example, cdf is a
2-column matrix with x values in column 1 and the estimate of the cdf
evaluated at x in column 2) and then take the first derivative over a
range of values to get density estimates.

The reason I don't want to use smooth.spline is that there is no way
to impose constraints (e.g. >=0, <=1, and monotonicity) as there is
with COBS.  However, since COBS doesn't have the 'deriv =' option, the
only way I can think of doing it with COBS is to evaluate the
derivatives numerically.

Regards,
Jim McDermott

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