detect_outliers_mad: Detect Outliers Using Median Absolute Deviation

In topolow: Force-Directed Euclidean Embedding of Dissimilarity Data

Detect Outliers Using Median Absolute Deviation

Description

Detects outliers in numeric data using the Median Absolute Deviation (MAD) method. This robust method is less sensitive to extreme values than standard deviation and works well for non-normally distributed data.

Usage

detect_outliers_mad(data, k = 3)

Arguments

data	Numeric vector of values to analyze
k	Numeric threshold for outlier detection (default: 3).

Details

The function calculates the median and MAD of the data and identifies points that are more than k MADs from the median as outliers.

Value

A list containing:

outlier_mask	Logical vector indicating outliers
stats	List containing: median: Median of data mad: Median absolute deviation n_outliers: Number of outliers detected

#' @importFrom stats median mad

topolow documentation built on Aug. 31, 2025, 1:07 a.m.