hdrbw: Highest Density Region Bandwidth

In hdrcde: Highest Density Regions and Conditional Density Estimation

Description

Estimates the optimal bandwidth for 1-dimensional highest density regions

Usage

hdrbw(x, HDRlevel, gridsize = 801, nMChdr = 1e+06, graphProgress = FALSE)

Arguments

x	Numerical vector containing data.
HDRlevel	HDR-level as defined in Hyndman (1996). Setting ‘HDRlevel’ equal to p (0<p<1) corresponds to a probability of 1-p of inclusion in the highest density region.
gridsize	the number of equally spaced points used for binned kernel density estimation.
nMChdr	the size of the Monte Carlo sample used for density quantile approximation of the highest density region, as described in Hyndman (1996).
graphProgress	logical flag: if ‘TRUE’ then plots showing the progress of the bandwidth selection algorithm are produced.

Details

This is a plug-in rule for bandwidth selection tailored to highest density region estimation

Value

A numerical vector of length 1.

Author(s)

Matt Wand

References

Hyndman, R.J. (1996). Computing and graphing highest density regions. The American Statistician, 50, 120-126.

Samworth, R.J. and Wand, M.P. (2010). Asymptotics and optimal bandwidth selection for highest density region estimation. The Annals of Statistics, 38, 1767-1792.

Examples

HDRlevelVal <- 0.55
x <- faithful$eruptions
hHDR <- hdrbw(x,HDRlevelVal)
HDRhat <- hdr.den(x,prob=100*(1-HDRlevelVal),h=hHDR)

Example output

This is hdrcde 3.3

hdrcde documentation built on Jan. 18, 2021, 9:05 a.m.