[R] Using spline parameters to generate data

[chumpmonkey3@hushmail.com]

# Sorry for the confussion.
# The way I had originally generated the data was
# sort of like this (cut and paste the code below a few times):

foo.curve <- runif(1,0.8,1.2) * exp(runif(1,-0.015,-0.005) * 1:500) +
runif(1,0.25,0.75) 
ts.plot(foo.curve, lwd = 2)

# where the min and max values in runif() were mined from the data using
nls.
# Are there similar ways to manipulate the smooth spline parameters to
give that kind of data?
# I still need a smooth line but would like the nugget, sill and range
to change 
# (to borrow terms from semivariance)

On Thu, 14 Aug 2003 17:46:28 -0700 Spencer Graves <spencer.graves at PDF.COM>
wrote:
>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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