doornik_hansen: Doornik-Hansen Test for Multivariate Normality

In MVN: Multivariate Normality Tests

Doornik-Hansen Test for Multivariate Normality

Description

Performs the Doornik–Hansen omnibus test by transforming the data to approximate normality and combining skewness and kurtosis measures to test for multivariate normality.

Usage

doornik_hansen(data, bootstrap = FALSE, B = 1000, cores = 1)

Arguments

data	A numeric matrix or data frame with observations in rows and variables in columns.
bootstrap	Logical; if TRUE, compute p-value via bootstrap resampling. Default is FALSE.
B	Integer; number of bootstrap replicates used when bootstrap = TRUE. Default is 1000.
cores	Integer; number of cores for parallel computation when bootstrap = TRUE. Default is 1.

Value

A data frame with one row containing the following columns: Test, the name of the test ("Doornik-Hansen"); Statistic, the value of the test statistic; df, the degrees of freedom; and p.value, the p-value from a chi-square approximation.

Examples

## Not run: 
data <- iris[1:50, 1:2]
dh_result <- doornik_hansen(data)
dh_result

## End(Not run)

MVN documentation built on June 10, 2025, 5:12 p.m.