Highest density regions for each observation

For a dist_kde object, determine which highest density region (HDR) each observation falls in, for one or more coverage probabilities. Some densities are multimodal, so the HDR for a given prob can consist of several disjoint regions; the returned columns identify the specific region (1, 2, ...) that each observation falls in, ordered from lowest to highest along the first variable, with NA for observations outside the HDR at that prob.

Usage

hdr_regions(object, prob)

Arguments

object

A dist_kde object, as returned by dist_kde(), containing a single distribution estimated from univariate or bivariate data.

prob

A numeric vector of probabilities giving the HDR coverage (between 0 and 1).

Value

A tibble containing the data used to estimate object, along with one additional integer column per element of prob (named hdr_<100*prob>) showing which region of the corresponding HDR each observation falls in.

See also

hdr_table, gg_hdrboxplot

Author

Rob J Hyndman

Examples

dist_kde(oldfaithful$duration) |> hdr_regions(c(0.5, 0.95))
#> # A tibble: 2,097 × 3
#>        x hdr_50 hdr_95
#>    <dbl>  <int>  <int>
#>  1   196     NA      2
#>  2   240      1      2
#>  3   121     NA      1
#>  4   240      1      2
#>  5   210     NA      2
#>  6   240      1      2
#>  7   205     NA      2
#>  8   214     NA      2
#>  9   240      1      2
#> 10   242      1      2
#> # ℹ 2,087 more rows
dist_kde(oldfaithful[, c("duration", "waiting")]) |> hdr_regions(0.90)
#> # A tibble: 2,097 × 3
#>    duration waiting hdr_90
#>       <dbl>   <dbl>  <int>
#>  1      196    5940     NA
#>  2      240    5820      2
#>  3      121    3900      1
#>  4      240    5280      2
#>  5      210    5580      2
#>  6      240    5760      2
#>  7      205    5160      2
#>  8      214    5400      2
#>  9      240    6060      2
#> 10      242    6060      2
#> # ℹ 2,087 more rows