Hns: Normal scale bandwidth

Description Usage Arguments Details Value References Examples

View source: R/selector.R

Description

Normal scale bandwidth.

Usage

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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

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

ks documentation built on April 22, 2018, 5:03 p.m.