Squared Mahalanobis distance
Definition taught in Covariance and the multivariate normal, part of Statistical learning
Squared Mahalanobis distance
| Type | Definition |
| Taught in | Covariance and the multivariate normal |
| Part | Statistical learning |
| Questions using it | 2 |
The squared Mahalanobis distance of \mathbf{X} from its mean is
(\mathbf{X}-\boldsymbol{\mu})^\top\Sigma^{-1}(\mathbf{X}-\boldsymbol{\mu}).
Used in
- Taught in Covariance and the multivariate normal, where the derivation and examples are.
- Also used in Estimation and inference for the multivariate normal · Statistical classifiers and discriminant analysis · High-dimensional analysis
- Questions that use it (2) — Random-walk Metropolis for a correlated normal (answer) · Axes of a contour (answer)
- All 8 questions on Covariance and the multivariate normal
See also
Joint distribution and density · Mean vector and covariance matrix · Correlation · Multivariate normal distribution · Linear images of a normal vector · Conditional distribution of a multivariate normal · Partial correlation · Random vectors