[R] Using spline parameters to generate data

[Spencer Graves]

Have you considered adding noise to "predict(spline.model)$y"?  If this 
won't solve your problem, then I think I don't understand what you want 
to do.

spencer graves

chumpmonkey3 at hushmail.com wrote:
> # 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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> 
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