lscv {locfit} | R Documentation |
The calling sequence for lscv
matches those for the
locfit
or locfit.raw
functions.
Note that this function is only designed for density estimation
in one dimension. The returned object contains the
least squares cross validation score for the fit.
The computation of int hat f(x)^2 dx is performed numerically. For kernel density estimation, this is unlikely to agree exactly with other LSCV routines, which may perform the integration analytically.
lscv(x, ..., exact=FALSE)
x |
model formula (or numeric vector, if exact=T ) |
... |
other arguments to locfit or
lscv.exact |
exact |
By default, the computation is approximate.
If exact=TRUE , exact computation using
lscv.exact is performed. This uses kernel density estimation
with a constant bandwidth. |
A vector consisting of the LSCV statistic and fitted degrees of freedom.
locfit
,
locfit.raw
,
lscv.exact
lscvplot
# approximate calculation for a kernel density estimate data(geyser) lscv(~geyser, alpha=cbind(0,1), ev="grid", mg=100, deg=0, flim=c(1,6), kern="gauss") # same computation, exact lscv(geyser,alpha=1,exact=TRUE)