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

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

In statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing...

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

Generalized canonical correlation Generalized chi-squared distribution Generalized Dirichlet distribution Generalized entropy index Generalized estimating...

Engineering Generalization error Generalized canonical correlation Generalized filtering Generalized iterative scaling Generalized multidimensional scaling Generative...

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

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

qn), where the p1, … pn and q1, … qn are the canonical coordinates (generalized momenta and generalized coordinates) of the system's internal degrees...

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

transformed into a block-diagonal form e.g. by means of a generalized Canonical Correlation Analysis (gCCA). Such a large matrix can thus be most effectively...

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

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

potentials. The partition function of the grand canonical ensemble defines the grand potential. A correlation function is introduced to describe the effective...

distribution. Poisson regression models are generalized linear models with the logarithm as the (canonical) link function, and the Poisson distribution...

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...

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

reports generalized nonlinear partial correlation coefficient between X and Y after removing the nonlinear effect of Z to be 0.8844. Also, the generalized nonlinear...

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

average (ARMA) model is assumed for the error variance, the model is a generalized autoregressive conditional heteroskedasticity (GARCH) model. ARCH models...

observational errors do not correlate between the data blocks. The generalized canonical correlation analysis (gCCA) is the statistical method of choice for making...

mere lack of correlation and is often not needed, although it can be exploited if it is known to hold.) Some methods such as generalized least squares...

{\displaystyle a_{ij}=b_{ij}=0} if i = j {\displaystyle i=j} .) Then the generalized correlation coefficient Γ {\displaystyle \Gamma } is defined as Γ = ∑ i , j...

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

one more invariant. These angles are called canonical or principal. The concept of angles can be generalized to pairs of flats in a finite-dimensional inner...

McCullagh, P.; Nelder, J. A. (January 1, 1983). "An outline of generalized linear models". Generalized Linear Models. Springer US. pp. 21–47. doi:10.1007/978-1-4899-3242-6_2...

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

variable is measured, a measure of statistical dependence such as a correlation coefficient A common collection of order statistics used as summary statistics...

z-transformation) of a Pearson correlation coefficient is its inverse hyperbolic tangent (artanh). When the sample correlation coefficient r is near 1 or...