Circular boxplot statistics (Tukey-like, for circular and axial data)

Computes the five-number summary and fences of a circular boxplot following Buttarazzi, Pandolfo & Porzio (2018): observations are depth-ranked outward from the antimedian, the box spans the central ~50 the median), and the fence multiplier is obtained in closed form from the von Mises quantiles at the sample's estimated concentration (so ~0.7 observations are flagged as far-out under that reference). Pairs with [add_circular_boxplot()] for rendering.

Usage

circ_boxplot_stats(hd, angle_col = "heading", axial = FALSE)

Source

Algorithm reimplemented from the bpDir package.

Arguments

hd

A data frame with a column of heading angles in radians (unit-circle convention), or a numeric vector of angles.

angle_col

Name of the angle column when `hd` is a data frame. Default `"heading"`.

axial

Logical. Treat the angles as axial (bidirectional, mod-pi): angles are doubled, the boxplot computed, and locations halved back to `[0, pi)`; the fence multiplier is taken on the doubled data. Default `FALSE`.

Value

A list with `median`, `antimedian`, `hinges`, `box_arc`, `constant`, `kappa`, `fences`, `whiskers`, `far_out` (all radians, unit-circle convention), `n`, `axial`, `drawable`, and `reason`. When `drawable` is `FALSE` (non-unique median or `n < 4`) the location fields are `NA`; `reason` may also carry a non-fatal advisory while `drawable` remains `TRUE` (near-uniform data).

References

Buttarazzi, D., Pandolfo, G. & Porzio, G. C. (2018). A boxplot for circular data. Biometrics 74(4), 1492–1501. doi:10.1111/biom.12889

See also

[add_circular_boxplot()], [circ_summarise()], [vonmises_fit()]

Examples

tr <- simulate_tracks(output = "trajset", seed = 1)
hd <- derive_headings(tr, rule = "distal")
circ_boxplot_stats(hd)
#> $median
#> [1] 6.146777
#> 
#> $antimedian
#> [1] 3.005184
#> 
#> $hinges
#> [1] 5.7343562 0.4583497
#> 
#> $box_arc
#> [1] 5.7343562 0.4583497
#> 
#> $constant
#> [1] 2.149198
#> 
#> $kappa
#> [1] 2.071822
#> 
#> $fences
#> [1] 3.569730 2.622976
#> 
#> $whiskers
#> [1] 4.167899 1.316886
#> 
#> $far_out
#> numeric(0)
#> 
#> $n
#> [1] 60
#> 
#> $axial
#> [1] FALSE
#> 
#> $drawable
#> [1] TRUE
#> 
#> $reason
#> [1] NA
#>