[R] Fitting spline using Pspline

[Ravi Varadhan]

Use the smooth.spline() function in "stats" package.  This is more stable.

?smooth.spline

Ravi.

________________________________________
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] On Behalf Of guy33 [david.reshef at magd.ox.ac.uk]
Sent: Sunday, May 29, 2011 1:30 PM
To: r-help at r-project.org
Subject: [R] Fitting spline using Pspline

Hey all,

I seem to be having trouble fitting a spline to a large set of data using
PSpline.  It seems to work fine for a data set of size n=4476, but not for
anything larger (say, n=4477).  For example:

THIS WORKS:
-----------------------------
random = array(0,c(4476,2))
random[,1] = runif(4476,0,1)
random[,2] = runif(4476,0,1)
random = random[order(random[,1]),]
plot(random[,1],random[,2])
fit2 = sm.spline(random[,1],random[,2], norder=2, cv=FALSE)
lines(fit2$x,fit2$y)

THIS FAILS:
-----------------------------
random = array(0,c(4477,2))
random[,1] = runif(4477,0,1)
random[,2] = runif(4477,0,1)
random = random[order(random[,1]),]
plot(random[,1],random[,2])
fit2 = sm.spline(random[,1],random[,2], norder=2, cv=FALSE)
lines(fit2$x,fit2$y)

It gives:
Error in smooth.Pspline(x = ux, y = tmp[, 1], w = tmp[, 2], method = method,
:
  Singularity error in solving equations

Does anyone know if this is just a limitation, or am I missing something.
The dataset I'd like to run it on contains n=6000.  If it is a limitation,
does anyone know of any other ways to do this that would accommodate a
larger dataset (ideally with generalized cross validation)?

Thanks!
-guy33

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