tukey_mc_up: Outlier detection threshold (upper)

In bigutilsr: Utility Functions for Large-scale Data

Description

Outlier detection threshold (upper) based on Tukey's rule, corrected for skewness using the 'medcouple', and possibly corrected for multiple testing.

Usage

tukey_mc_up(x, coef = NULL, alpha = 0.05, a = -4, b = 3)

Arguments

x	Numeric vector. Should be somewhat normally distributed.
coef	number determining how far 'whiskers' extend out from the box. If NULL (default), this is computed to get an type-I error of alpha, after adjusting for multiple testing. A standard value to use is 1.5.
alpha	See coef. Default is 0.05.
a	scaling factors multiplied by the medcouple mc() to determine outlyer boundaries; see the references.
b	scaling factors multiplied by the medcouple mc() to determine outlyer boundaries; see the references.

References

Hubert, M. and Vandervieren, E. (2008). An adjusted boxplot for skewed distributions, Computational Statistics and Data Analysis 52, 5186–5201.

See Also

robustbase::adjbox()

Examples

hist(x <- c(rnorm(3, m = 6), rnorm(1e4, m = 0)))
(q <- tukey_mc_up(x))
abline(v = q, col = "red")
which(x > q)

bigutilsr documentation built on April 14, 2021, 1:06 a.m.