If you can put up with using gam in package mgcv to fit your splines
then you can get SEs on the spline derivatives as shown in the final
example in the help file for plot.gam. (gam uses reduced rank smoothing
splines, so you may need to up the `k' parameter for the smooth terms to
ensure that the rank is not too small for your data).
On 08/06/2011 01:59 AM, Bingzhang Chen wrote:
Dear all,
I want to use smooth.spline to construct a cubic smoothing spline and its first
derivative to my data. However, the predict.smooth.spline does not seem to
provide a SE for both the fitted values and their derivatives. How should I
calculate it?
Thank you very much,
Bingzhang
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