Calculate highest density regions continuously over some conditioned variable.

Calculates and plots highest density regions for a conditional density estimate. Uses output from cde().

Usage

hdr.cde(den, prob = c(0.5, 0.95, 0.99), plot = TRUE, nn = 1000, ...)

Arguments

den: Conditional density in the same format as the output from cde().
prob: Probability coverage level for HDRs
plot: Should HDRs be plotted? If FALSE, results are returned.
nn: Number of points to be sampled from each density when estimating the HDRs.
...: Other arguments passed to plot.hdrcde().

Value

hdr: array (a,b,c) where where a specifies conditioning value, b gives the HDR endpoints and c gives the probability coverage.
modes: estimated mode of each conditional density

The result is returned invisibly if plot=TRUE.

References

Hyndman, R.J., Bashtannyk, D.M. and Grunwald, G.K. (1996) "Estimating and visualizing conditional densities". Journal of Computational and Graphical Statistics, 5, 315-336.

Author

Rob J Hyndman

Examples

faithful.cde <- cde(faithful$waiting, faithful$eruptions)
faithful.hdr <- hdr.cde(faithful.cde, prob = c(0.50, 0.95))

faithful.hdr
#> HDRs for conditional density estimate:
#>    faithful$eruptions | faithful$waiting 
#> Conditioning values: 43.00, 46.79, 50.57, 54.36, 58.14, 61.93, 65.71, 69.50, 73.29, 77.07, 80.86, 84.64, 88.43, 92.21, 96.00 
#> Levels:  50%, 95% 
plot(faithful.hdr, xlab = "Waiting time", ylab = "Duration time")