[R] Using spline parameters to generate data

[chumpmonkey3@hushmail.com]

# I need to generate some data. I'm modeling some time series that follow
a
# negative exponential decay (mostly). I have 20 samples that can easily
be fit with cubic splines.
# What I want to do is generate many thousands of similar samples using
the parameters from the splines

# For instance one data sample looks not unlike this:
foo.curve <- 1 * exp(-0.01 * 1:500) + 0.5 
ts.plot(foo.curve, lwd = 2)

# Another sample looks not unlike this:
foo.curve2 <- 0.9 * exp(-0.02 * 1:500) + 0.5 
ts.plot(foo.curve2, lwd = 2)



# They can be fit with splines easily like so:

ts.plot(foo.curve, lwd = 2)
spline.model <- smooth.spline(foo.curve)

fits4foo <- predict(spline.model)$y
spline4foo <- spline(1:500, fits4foo)
lines(spline4foo$x, spline4foo$y, col = "red", lwd = 2, lty = "dashed")

# I originally generated the data I needed by using a nls model and 
# adding some noise to the mean of the coefficents from those fits.
# However, I've been told to try and do this using splines for arcane
reasons.

# So, if you had 20 splines like spline.model above and wanted to generate
some similar data what would you do?
# Thanks in advance.









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