Hscv {ks}R Documentation

Smoothed cross-validation (SCV) bandwidth matrix selector for bivariate data

Description

SCV bandwidth matrix for 2- to 6-dimensional data.

Usage

Hscv(x, pre="sphere", Hstart, binned=FALSE, bgridsize)

Arguments

x matrix of data values
pre "scale" = pre-scaling, "sphere" = pre-sphering
Hstart initial bandwidth matrix, used in numerical optimisation
binned flag for binned kernel estimation
bgridsize vector of binning grid sizes - required only if binned=TRUE

Details

This SCV selector is a generalisation of the univariate SCV selector of Jones, Marron & Park (1991).

For d = 1, 2, 3, 4 and binned=TRUE, the density estimate is computed over a binning grid defined by bgridsize. Otherwise it's computed exactly.

For details on the pre-transformations in pre, see pre.sphere and pre.scale.

If Hstart is not given then it defaults to k*var(x) where k = 4/(n*(d + 2))^(2/(d+ 4)), n = sample size, d = dimension of data.

Value

Full SCV bandwidth matrix. Please note that a diagonal version of this selector is not available.

References

Jones, M.C., Marron, J.~S. & Park, B.U. (1991) A simple root n bandwidth selector. The Annals of Statistics 19, 1919–1932.

Duong, T. & Hazelton, M.L. (2005) Cross-validation bandwidth matrices for multivariate kernel density estimation. Scandinavian Journal of Statistics. 32, 485-506.

See Also

Hlscv, Hbcv

Examples

data(unicef)
Hscv(unicef)
Hscv(unicef, binned=TRUE)

[Package ks version 1.4.9 Index]