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Tukey's Five Number Summary for tf vectors

Source: R/summarize.R
fivenum.Rd

Computes a depth-based five number summary for functional data: the observations with minimum, lower-hinge, median, upper-hinge, and maximum depth values.

Usage

fivenum(x, na.rm = FALSE, ...)

# Default S3 method
fivenum(x, na.rm = FALSE, ...)

# S3 method for class 'tf'
fivenum(x, na.rm = FALSE, depth = "MHI", ...)

Arguments

x

a tf vector (or numeric for the default method).

na.rm

logical; if TRUE, NA observations are removed first.

...

passed to tf_depth().

depth

depth method for ordering. See tf_depth(). Defaults to "MHI" for an up-down ordering.

Value

fivenum.tf: a named tf vector of length 5.
fivenum.default: see stats::fivenum().

See also

Other tidyfun summary functions: functionwise, tfsummaries

Examples

set.seed(1)
f <- tf_rgp(7)
fivenum(f)
#> tfd[5]: [0,1] -> [-2.191315,2.185118] based on 51 evaluations each
#> interpolation by tf_approx_linear 
#> min        : ▅▅▅▅▄▄▃▃▂▂▂▂▂▂▂▃▃▃▄▄▄▄▅▅▅▅
#> lower_hinge: ▆▆▆▆▆▆▅▅▅▄▄▃▃▃▂▂▁▁▁▁▁▁▁▁▂▂
#> median     : ▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▅▆▆▆▇▇▇████
#> upper_hinge: ▃▄▄▅▆▆▇▇████▇▇▇▆▆▅▅▅▅▅▅▅▆▆
#> max        : ▆▆▆▆▇▆▆▆▆▅▅▅▅▅▅▅▅▅▆▆▆▆▅▅▄▄