The cross-correlation matrix of two random vectors is a matrix containing as elements the cross-correlations of all pairs of elements of the random vectors...

In signal processing, cross-correlation is a measure of similarity of two series as a function of the displacement of one relative to the other. This...

variable and the j th one. Likewise, the correlations can be placed in a correlation matrix. In the case of a time series which is stationary in the wide sense...

Autocorrelation, sometimes known as serial correlation in the discrete time case, measures the correlation of a signal with a delayed copy of itself....

In probability theory and statistics, a cross-covariance matrix is a matrix whose element in the i, j position is the covariance between the i-th element...

covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the...

]\operatorname {E} [\mathbf {X} ]^{T}} . Similarly for the cross-correlation matrix and the cross-covariance matrix: R X Y = K X Y + E ⁡ [ X ] E ⁡ [ Y ] T {\displaystyle...

by these two fixed locations. Autoregressive process Correlation Cross-covariance Cross-correlation Noise covariance estimation (as an application example)...

data) one wants to find the "nearest" correlation matrix to an "approximate" correlation matrix (e.g., a matrix which typically lacks semi-definite positiveness...

[X_{t_{1}}Y_{t_{2}}]-\mu _{X}(t_{1})\mu _{Y}(t_{2}).\,} Cross-covariance is related to the more commonly used cross-correlation of the processes in question. In the case...

made up of autocorrelations. Correlation functions of different random variables are sometimes called cross-correlation functions to emphasize that different...

statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices...

In statistics, the Pearson correlation coefficient (PCC) is a correlation coefficient that measures linear correlation between two sets of data. It is...

different matrix. PCA is also related to canonical correlation analysis (CCA). CCA defines coordinate systems that optimally describe the cross-covariance...

obtain a sample partial correlation). Note that only a single matrix inversion is required to give all the partial correlations between pairs of variables...

statistics, a contingency table (also known as a cross tabulation or crosstab) is a type of table in a matrix format that displays the multivariate frequency...

\begin{array}{ccc}1&2&3\\2&5&8\\3&8&6\end{array}}\right].} The cross correlation matrix C Y X {\displaystyle C_{YX}} is defined as C Y X = [ E [ z 4 ,...

covariance matrix, the genetic correlation is computed by standardizing this, i.e., by converting the covariance matrix to a correlation matrix. Generally...

Two dimensional correlation analysis is a mathematical technique that is used to study changes in measured signals. As mostly spectroscopic signals are...

correlation for all the stocks and create a cross correlation matrix C i j {\displaystyle Cij} . The cross correlation is between stock i {\displaystyle i} and...

of describing the confusion matrix of true and false positives and negatives by a single number, the Matthews correlation coefficient is generally regarded...

reduced correlation matrix reproduces the correlation matrix as nearly as possible, except for the diagonal elements of the correlation matrix which are...

DTFT of a finite length sequence. (§ Sampling the DTFT) It is the cross correlation of the input sequence, x n {\displaystyle x_{n}} , and a complex sinusoid...

(2008-04-01). "Improved shrinkage estimation of squared multiple correlation coefficient and squared cross-validity coefficient". Organizational Research Methods...

In statistics, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman and often denoted by the Greek letter ρ {\displaystyle...

P {\displaystyle P} is the correlation matrix and V {\displaystyle V} the diagonal variance matrix. Whitening a data matrix follows the same transformation...

be extended to compute autocorrelation, cross-correlation, moving average etc. A bi-infinite Toeplitz matrix (i.e. entries indexed by Z × Z {\displaystyle...

probability theory and mathematical physics, a random matrix is a matrix-valued random variable—that is, a matrix in which some or all of its entries are sampled...

output. Often, a correlation-style matrix of dot products provides the re-weighting coefficients. In the figures below, W is the matrix of context attention...

estimated correlations having absolute values which are greater than one, and/or a non-invertible covariance matrix. When estimating the cross-covariance...