ThmDex – An index of mathematical definitions, results, and conjectures.
Set of symbols
Alphabet
Deduction system
Theory
Zermelo-Fraenkel set theory
Set
Binary cartesian set product
Binary relation
Map
Simple map
Simple function
Measurable simple complex function
Simple integral
Unsigned basic integral
Unsigned basic expectation
Basic expectation
Random real number moment
Random real number central moment
Joint central moment
Definition D2011
Euclidean real covariance
Formulation 0
Let $X, Y \in \text{Random}(\mathbb{R}^{N \times 1})$ each be a D5210: Random real column matrix such that
(i) \begin{equation} \mathbb{E} |X|^2, \mathbb{E} |Y|^2 < \infty \end{equation}
The covariance of $(X, Y)$ is the D4571: Real matrix \begin{equation} \mathbb{E} \left[ (X - \mathbb{E} X) (Y - \mathbb{E} Y)^T \right] \end{equation}
Formulation 1
Let $X, Y \in \text{Random}(\mathbb{R}^N)$ each be a D4383: Random euclidean real number such that
(i) \begin{equation} \mathbb{E} |X|^2, \mathbb{E} |Y|^2 < \infty \end{equation}
The covariance of $(X, Y)$ is the D4571: Real matrix \begin{equation} \begin{bmatrix} \mathbb{E}[(X_1 - \mathbb{E} X_1) (Y_1 - \mathbb{E} Y_1)] & \mathbb{E}[(X_1 - \mathbb{E} X_1) (Y_2 - \mathbb{E} Y_2)] & \cdots & \mathbb{E}[(X_1 - \mathbb{E} X_1) (Y_N - \mathbb{E} Y_N)] \\ \mathbb{E}[(X_2 - \mathbb{E} X_2) (Y_1 - \mathbb{E} Y_1)] & \mathbb{E}[(X_2 - \mathbb{E} X_2) (Y_2 - \mathbb{E} Y_2)] & \vdots & \mathbb{E}[(X_2 - \mathbb{E} X_2) (Y_N - \mathbb{E} Y_N)] \\ \vdots & \cdots & \ddots & \vdots \\ \mathbb{E}[(X_N - \mathbb{E} X_N) (Y_1 - \mathbb{E} Y_1)] & \mathbb{E}[(X_N - \mathbb{E} X_N) (Y_2 - \mathbb{E} Y_2)] & \cdots & \mathbb{E}[(X_N - \mathbb{E} X_N) (Y_N - \mathbb{E} Y_N)] \end{bmatrix} \end{equation}
Children
Euclidean real variance