MVN
  • Get Started
  • Tutorials
    • Multivariate Normality Tests
    • Univariate Normality & Descriptive Statistics
    • Multivariate Outlier Detection
    • Diagnostic Visualizations
    • Data Transformation Techniques
    • Subset Analysis
    • Handling Missing Data
  • Reference

On this page

  • MVN: Multivariate Normality in a Single Function
  • Minimal Working Example
  • What’s Next?

MVN: Multivariate Normality in a Single Function

A one-stop R package for testing, diagnostics, and visualization of multivariate normality.

Minimal Working Example

# Load the package:
library(MVN)
# First two columns of iris as an example
df <- iris[1:50,1:2]
# Runs the Henze–Zirkler test by default
result <- mvn(data = df)
summary(result, select = "mvn")
── Multivariate Normality Test Results ─────────────────────────────────────────
           Test Statistic p.value     Method      MVN
1 Henze-Zirkler     0.286   0.915 asymptotic ✓ Normal

What’s Next?

Dive into Tutorials to learn step by step, or check out the Reference for detailed documentation of all functions.

© 2025 MVN package

 

Built with Quarto