hdrconf: HDRs with confidence intervals

In hdrcde: Highest Density Regions and Conditional Density Estimation

Description

Calculates Highest Density Regions with confidence intervals.

Usage

hdrconf(x, den, prob = 95, conf = 95)

Arguments

x	Numeric vector containing data.
den	Density of data as list with components x and y.
prob	Probability coverage for for HDRs.
conf	Confidence for limits on HDR.

Value

hdrconf returns list containing the following components:

hdr	Highest density regions
hdr.lo	Highest density regions corresponding to lower confidence limit.
hdr.hi	Highest density regions corresponding to upper confidence limit.
falpha	Values of f[alpha] corresponding to HDRs.
falpha.ci	Values of f[alpha] corresponding to lower and upper limits.

Author(s)

Rob J Hyndman

References

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

See Also

hdr, plot.hdrconf

Examples

x <- c(rnorm(100,0,1),rnorm(100,4,1))
den <- density(x,bw=hdrbw(x,50))
trueden <- den
trueden$y <- 0.5*(exp(-0.5*(den$x*den$x)) + exp(-0.5*(den$x-4)^2))/sqrt(2*pi)
sortx <- sort(x)

par(mfcol=c(2,2))
for(conf in c(50,95))
{
  m <- hdrconf(sortx,trueden,conf=conf)
  plot(m,trueden,main=paste(conf,"% HDR from true density"))
  m <- hdrconf(sortx,den,conf=conf)
  plot(m,den,main=paste(conf,"% HDR from empirical density\n(n=200)"))
}

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