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

In statistics, the generalized canonical correlation analysis (gCCA), is a way of making sense of cross-correlation matrices between the sets of random...

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

canonical correlation analysis (DCCA), introduced in 2013, employs neural networks to learn nonlinear transformations for maximizing the correlation between...

component analysis (ICA), linear discriminant analysis (LDA) and canonical correlation analysis (CCA). Multilinear methods may be causal in nature and...

Autocorrelation Canonical correlation Coefficient of determination Cointegration Concordance correlation coefficient Cophenetic correlation Correlation disattenuation...

of criterion variables by the canonical correlations ρ1, ρ2, ..., and by the sets of canonical weights C and D. Canonical analysis belongs to a group of...

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

Regularized canonical correlation analysis is a way of using ridge regression to solve the singularity problem in the cross-covariance matrices of canonical correlation...

A correlation coefficient is a numerical measure of some type of linear correlation, meaning a statistical relationship between two variables. The variables...

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

eigenvectors of a slightly different matrix. PCA is also related to canonical correlation analysis (CCA). CCA defines coordinate systems that optimally describe...

observed variables. Canonical correlation analysis finds linear relationships among two sets of variables; it is the generalised (i.e. canonical) version of bivariate...

Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization...

for a non-parametric alternative Discriminant function analysis Canonical correlation analysis Multivariate analysis of variance (Wikiversity) Repeated...

equivalent to any form of multiple regression analysis, factor analysis, canonical correlation analysis, discriminant analysis, as well as more general families...

two binary variables. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class)...

of canonical correlation and were originally computed using SVD of corresponding covariance matrices. However, as first noticed in, the canonical correlation...

of descriptive statistics. Canonical correlation Coding (social sciences) Descriptive statistics Discriminant correlation analysis (DCA) Earl R. Babbie...

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...

nonlinear interactions. Both distance correlation and kernel-based metrics can be used in methods such as canonical correlation analysis and independent component...

heterogeneous data integration called "Regularized Generalized Canonical Correlation Analysis" (RGCCA ) enables identifying such putative biomarkers...

statistics Multivariate Regression Manova Principal components Canonical correlation Discriminant analysis Cluster analysis Classification Structural...

statistical calibration problem Cancer cluster Candlestick chart Canonical analysis Canonical correlation Canopy clustering algorithm Cantor distribution Carpet...

distribution is said to be in canonical form (or natural form). Note that any distribution can be converted to canonical form by rewriting θ {\displaystyle...

Delphi method Statistical techniques include: Regression analysis Canonical correlation Causal analysis Multilevel models Factor analysis Linear discriminant...

statistics Multivariate Regression Manova Principal components Canonical correlation Discriminant analysis Cluster analysis Classification Structural...

A percentile or quartile measure is used for measuring dispersion. Correlations are restricted to various rank order methods. Measures of statistical...

non-directional formula for the rank-biserial correlation was provided by Wendt, such that the correlation is always positive. Pairwise comparisons Condorcet...

formal analysis in a 1918 article on theoretical population genetics, The Correlation Between Relatives on the Supposition of Mendelian Inheritance. His first...