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Test for outliers in a numeric vector

Source: R/test_outlier.R
test_outlier.Rd

[Stable]

test_outlier() identifies outliers in a numeric vector using either the interquartile range (IQR) method or the standard deviation (SD) method.

Usage

test_outlier(x, method = "iqr", iqr_mult = 1.5, sd_mult = 3)

Arguments

x

A numeric vector to test for outliers.

method

(Optional) A character string specifying the outlier detection method. Must be either "iqr" for interquartile range method or "sd" for standard deviation method (Default: "iqr").

iqr_mult

(Optional) A numeric multiplier for the IQR threshold (Default: 1.5).

sd_mult

(Optional) A numeric multiplier for the standard deviation threshold (Default: 3).

Value

A logical vector of the same length as x with TRUE for outliers and FALSE for non-outliers.

Details

When using the "iqr" method, values are considered outliers if they are below Q1 - (iqr_mult * IQR) or above Q3 + (iqr_mult * IQR), where Q1 is the first quartile, Q3 is the third quartile, and IQR is the interquartile range.

When using the "sd" method, values are considered outliers if they are below mean - (sd_mult * SD) or above mean + (sd_mult * SD), where SD is the standard deviation.

See also

Other statistical functions: cut_interval_mean(), remove_outliers(), std_error()

Examples

test_outlier(c(1, 2, 3, 4, 5), method = "iqr")
#> [1] FALSE FALSE FALSE FALSE FALSE
#> [1] FALSE FALSE FALSE FALSE FALSE # Expected

test_outlier(c(1, 2, 3, 4, 10), method = "iqr")
#> [1] FALSE FALSE FALSE FALSE  TRUE
#> [1] FALSE FALSE FALSE FALSE  TRUE # Expected

test_outlier(c(1, 5, 6, 7, 10), method = "iqr", iqr_mult = 1)
#> [1]  TRUE FALSE FALSE FALSE  TRUE
#> [1]  TRUE FALSE FALSE FALSE  TRUE # Expected

test_outlier(c(1, 2, 3, 4, 5), method = "sd", sd_mult = 1)
#> [1]  TRUE FALSE FALSE FALSE  TRUE
#> [1] TRUE FALSE FALSE FALSE  TRUE # Expected

test_outlier(c(1, 2, 3, 4, 100), method = "sd", sd_mult = 1)
#> [1] FALSE FALSE FALSE FALSE  TRUE
#> [1] FALSE FALSE FALSE FALSE  TRUE # Expected