Generalized variance
The generalized variance is a scalar value which generalizes variance for multivariate random variables. It was introduced by Samuel S. Wilks.
The generalized variance is defined as the determinant of the covariance matrix, . It can be shown to be related to the multidimensional scatter of points around their mean.[1]
Minimizing the generalized variance gives the Kalman filter gain.[2]
References
[edit]- ↑ Kocherlakota, S.; Kocherlakota, K. (2004). "Generalized Variance". Encyclopedia of Statistical Sciences. Wiley Online Library. doi:10.1002/0471667196.ess0869. ISBN 0471667196. Retrieved 30 October 2019.
- ↑ Proof that the Kalman gain minimizes the generalized variance, Eviatar Bach https://arxiv.org/abs/2103.07275
 | This statistics-related article is a stub. You can help Wikipedia by adding missing information. |