mv_outlier: Identify Multivariate Outliers via Robust Mahalanobis...

In MVN: Multivariate Normality Tests

Identify Multivariate Outliers via Robust Mahalanobis Distances

Description

Computes robust Mahalanobis distances for multivariate data using the Minimum Covariance Determinant (MCD) estimator, flags outliers based on either a chi-square quantile cutoff or an adjusted cutoff using the Atkinson–Riani–Welsh (ARW) method, and optionally generates a Mahalanobis Q–Q plot.

Usage

mv_outlier(
  data,
  outlier = TRUE,
  qqplot = TRUE,
  alpha = 0.05,
  method = c("quan", "adj"),
  seed = NULL,
  label = TRUE,
  title = "Chi-Square Q-Q Plot"
)

Arguments

data	A numeric matrix or data frame with observations in rows and at least two numeric columns.
outlier	Logical; if TRUE, includes the Mahalanobis distance values and outlier classification in the output. If FALSE, suppresses this component. Default is TRUE.
qqplot	Logical; if TRUE, a Chi-Square Q–Q plot is generated to visualize outlier detection. Default is TRUE.
alpha	Numeric; significance level used for the adjusted cutoff method (only applies if method = "adj"). Default is 0.05.
method	Character string specifying the outlier detection method. Must be either "quan" (quantile-based cutoff) or "adj" (adjusted cutoff via ARW). Default is "quan".
seed	Optional integer to set the random seed for reproducibility of the MCD estimator. If NULL, the seed is not set.
label	Logical; if TRUE and qqplot = TRUE, labels the detected outliers in the plot. Default is TRUE.
title	Optional character string specifying the title for the Q–Q plot. Default is "Chi-Square Q-Q Plot".

Value

A list containing the following components: outlier, a data frame of Mahalanobis distances with observation IDs and outlier flags (if outlier = TRUE); qq_outlier_plot, a ggplot object of the Mahalanobis Q–Q plot (if qqplot = TRUE); and newData, a data frame of non-outlier observations.

Examples

## Not run: 
data <- iris[, 1:4]
res <- mv_outlier(data, method = "adj", alpha = 0.025)
res$outlier
res$qq_outlier_plot
head(res$newData)

## End(Not run)

MVN documentation built on Jan. 13, 2026, 9:07 a.m.