R: HDRs with confidence intervals

hdrconf {hdrcde} | R Documentation

## HDRs with confidence intervals

### 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)"))
    }

[Package hdrcde version 3.4 Index]