Predict method for COBS Fits
Compute predicted values and simultaneous or pointwise confidence
bounds for cobs objects.
## S3 method for class 'cobs'
predict(object, z, deriv = 0L,
minz = knots[1], maxz = knots[nknots], nz = 100,
interval = c("none", "confidence", "simultaneous", "both"),
level = 0.95, ...)object |
object of class |
z |
vector of grid points at which the fitted values are
evaluated; defaults to an equally spaced grid with |
deriv |
scalar integer specifying (the order of) the derivative that should be computed. |
minz |
numeric needed if |
maxz |
analogous to |
nz |
number of grid points in |
interval |
type of interval calculation, see below |
level |
confidence level |
... |
further arguments passed to and from methods. |
a matrix of predictions and bounds if interval is set (not
"none"). The columns are named z, fit, further
cb.lo and cb.up for the simultaneous confidence
band, and ci.lo and ci.up the pointwise
confidence intervals according to specified level.
If z has been specified, it is unchanged in the result.
Martin Maechler, based on He and Ng's code in cobs().
cobs the model fitting function.
example(cobs) # continuing :
(pRbs <- predict(Rbs))
#str(pSbs <- predict(Sbs, xx, interval = "both"))
str(pSbs <- predict(Sbs, xx, interval = "none"))
plot(x,y, xlim = range(xx), ylim = range(y, pSbs[,2], finite = TRUE),
main = "COBS Median smoothing spline, automatical lambda")
lines(pSbs, col = "red")
lines(spline(x,f.true), col = "gray40")
#matlines(pSbs[,1], pSbs[,-(1:2)],
# col= rep(c("green","blue"),c(2,2)), lty=2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.