Trimmed Quantiles

For data \(X = x_1, x_2, \ldots, x_n\), with order statistics \(x_{(1)}, x_{(2)}, \ldots, x_{(r)}\) return the quantiles for a trimmed data set, e.g., \(\boldsymbol{X} \backslash \{x_{(1)}, x_{(r)}\}\) (trim = 1), or \(\boldsymbol{X} \backslash \{x_{(1)}, x_{(2)}, x_{(r-1)}, x_{(r)}\}\) (trim = 2).

Usage

trimmed_quantile(x, trim = 1L, use_unique = TRUE, ...)

Arguments

x

a numeric vector

trim

defaults to 1, omitting the min and the max

use_unique

logical, if true (defaults), base the quantiles on unique values, if false, base the quantiles on all data, after trimming.

...

other arguments to pass to stats::quantile

Value

a numeric vector, the return from quantile

See also

quantile

Examples

trimmed_quantile(1:100, prob = 1:23 / 24, name = FALSE)
#>  [1]  6.041667 10.083333 14.125000 18.166667 22.208333 26.250000 30.291667
#>  [8] 34.333333 38.375000 42.416667 46.458333 50.500000 54.541667 58.583333
#> [15] 62.625000 66.666667 70.708333 74.750000 78.791667 82.833333 86.875000
#> [22] 90.916667 94.958333

# Warning
# trimmed_quantile(1:100, trim = .3, prob = 1:23 / 24, name = FALSE)

# no warning
trimmed_quantile(1:100, trim = 3, prob = 1:23 / 24, name = FALSE)
#>  [1]  7.875 11.750 15.625 19.500 23.375 27.250 31.125 35.000 38.875 42.750
#> [11] 46.625 50.500 54.375 58.250 62.125 66.000 69.875 73.750 77.625 81.500
#> [21] 85.375 89.250 93.125