---
title: "Robust Covariance in JavaScript with @kanaries/ml"
description: "Estimate robust covariance and detect multivariate outliers in JavaScript or TypeScript with MinCovDet and EllipticEnvelope from @kanaries/ml."
canonical_url: "https://ml.kanaries.net/docs/apis/covariance"
markdown_url: "https://ml.kanaries.net/docs/apis/covariance/index.html.md"
---
# Robust covariance in JavaScript

Robust covariance estimators describe the center and spread of multivariate data without letting a small number of extreme observations dominate the result. They are useful for anomaly detection, robust distance calculations, and preprocessing noisy tabular data.

`@kanaries/ml` provides browser- and Node.js-ready TypeScript implementations of FAST-MCD through [MinCovDet](/docs/apis/covariance/minCovDet.md) and its anomaly-detection wrapper [EllipticEnvelope](/docs/apis/covariance/ellipticEnvelope.md).

Choose `MinCovDet` when you need robust location, covariance, support masks, or Mahalanobis distances. Choose `EllipticEnvelope` when you need `predict`, `scoreSamples`, and `decisionFunction` with a contamination threshold.

For classical, shrinkage, and sparse inverse covariance, see [Covariance Estimators](/docs/apis/covariance/covarianceEstimators.md).