Hns: Normal scale bandwidth

In ks: Kernel Smoothing

Normal scale bandwidth

Description

Normal scale bandwidth.

Usage

Hns(x, deriv.order=0)
Hns.diag(x)
hns(x, deriv.order=0)
Hns.kcde(x)
hns.kcde(x)

Arguments

x	vector/matrix of data values
deriv.order	derivative order

Details

Hns is equal to (4/(n*(d+2*r+2)))^(2/(d+2*r+4))*var(x), n = sample size, d = dimension of data, r = derivative order. hns is the analogue of Hns for 1-d data. These can be used for density (derivative) estimators kde, kdde. The equivalents for distribution estimators kcde are Hns.kcde and hns.cde.

Value

Normal scale bandwidth.

References

Chacon J.E., Duong, T. & Wand, M.P. (2011). Asymptotics for general multivariate kernel density derivative estimators. Statistica Sinica, 21, 807-840.

Examples

data(forbes, package="MASS")
Hns(forbes, deriv.order=2)
hns(forbes$bp, deriv.order=2)

ks documentation built on Sept. 30, 2024, 9:15 a.m.