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...

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

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

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...

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

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

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

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

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

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

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

measures, however, this is generally not supported. Instead, the canonical correlation is the preferred measure of effect size. It is similar to the eigenvalue...

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...

"probability plot correlation coefficient" (PPCC plot) is the correlation coefficient between the paired sample quantiles. The closer the correlation coefficient...

In statistics, the Kendall rank correlation coefficient, commonly referred to as Kendall's τ coefficient (after the Greek letter τ, tau), is a statistic...

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...

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...

related to the covariance matrix is the matrix of Pearson product-moment correlation coefficients between each of the random variables in the random vector...

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)...

characteristics of the data (estimation), describing associations within the data (correlation), and modeling relationships within the data (for example, using regression...

(SVM), Gaussian processes, principal components analysis (PCA), canonical correlation analysis, ridge regression, spectral clustering, linear adaptive...

distributed species optima and site scores. Canonical correlation analysis (CANCOR) ter Braak, Cajo J. F. (1986). "Canonical Correspondence Analysis: A New Eigenvector...

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

parameters Coefficient of variation Cumulant Deviation (statistics) Distance correlation Distance standard deviation Error bar Geometric standard deviation Mahalanobis...

calculate a county average). For example, it might be true that there is no correlation between infant mortality and family income at the city level, while still...

the Theory of Contingency and Its Relation to Association and Normal Correlation", part of the Drapers' Company Research Memoirs Biometric Series I published...

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