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  2. Covariance matrix - Wikipedia

    en.wikipedia.org/wiki/Covariance_matrix

    An entity closely related to the covariance matrix is the matrix of Pearson product-moment correlation coefficients between each of the random variables in the random vector , which can be written as ⁡ = (⁡ ()) (⁡ ()), where ⁡ is the matrix of the diagonal elements of (i.e., a diagonal matrix of the variances of for =, …,).

  3. Cross-correlation matrix - Wikipedia

    en.wikipedia.org/wiki/Cross-correlation_matrix

    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. The cross-correlation matrix is used in various digital signal processing algorithms.

  4. Correlation function (statistical mechanics) - Wikipedia

    en.wikipedia.org/wiki/Correlation_function...

    One common correlation function is the radial distribution function which is seen often in statistical mechanics and fluid mechanics. The correlation function can be calculated in exactly solvable models (one-dimensional Bose gas, spin chains, Hubbard model) by means of Quantum inverse scattering method and Bethe ansatz. In an isotropic XY ...

  5. Cross-correlation - Wikipedia

    en.wikipedia.org/wiki/Cross-correlation

    In time series analysis and statistics, the cross-correlation of a pair of random process is the correlation between values of the processes at different times, as a function of the two times. Let ( X t , Y t ) {\displaystyle (X_{t},Y_{t})} be a pair of random processes, and t {\displaystyle t} be any point in time ( t {\displaystyle t} may be ...

  6. Canonical correlation - Wikipedia

    en.wikipedia.org/wiki/Canonical_correlation

    In statistics, canonical-correlation analysis (CCA), also called canonical variates analysis, is a way of inferring information from cross-covariance matrices.If we have two vectors X = (X 1, ..., X n) and Y = (Y 1, ..., Y m) of random variables, and there are correlations among the variables, then canonical-correlation analysis will find linear combinations of X and Y that have a maximum ...

  7. Estimation of covariance matrices - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_covariance...

    The sample covariance matrix (SCM) is an unbiased and efficient estimator of the covariance matrix if the space of covariance matrices is viewed as an extrinsic convex cone in R p×p; however, measured using the intrinsic geometry of positive-definite matrices, the SCM is a biased and inefficient estimator. [1]

  8. Cross-covariance matrix - Wikipedia

    en.wikipedia.org/wiki/Cross-covariance_matrix

    where = ⁡ [] and = ⁡ [] are vectors containing the expected values of and .The vectors and need not have the same dimension, and either might be a scalar value.. The cross-covariance matrix is the matrix whose (,) entry is the covariance

  9. Correlation function - Wikipedia

    en.wikipedia.org/wiki/Correlation_function

    A correlation function is a function that gives the statistical correlation between random variables, contingent on the spatial or temporal distance between those variables. [1] If one considers the correlation function between random variables representing the same quantity measured at two different points, then this is often referred to as an ...