Displaying 1 result from an estimated 1 matches for "fits4foo".
2003 Aug 14
2
Using spline parameters to generate data
...* 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...