lscv {locfit} | R Documentation |

## Least Squares Cross Validation Statistic.

### Description

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.

### Usage

lscv(x, ..., exact=FALSE)

### Arguments

`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. |

### Value

A vector consisting of the LSCV statistic and fitted degrees of freedom.

### See Also

`locfit`

,
`locfit.raw`

,
`lscv.exact`

`lscvplot`

### Examples

# 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)

[Package

*locfit* version 1.1-9

Index]