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  2. 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 ...

  3. Regularized canonical correlation analysis - Wikipedia

    en.wikipedia.org/wiki/Regularized_canonical...

    The idea probably dates back to Hrishikesh D. Vinod's publication in 1976 where he called it "Canonical ridge". [1] [2] It has been suggested for use in the analysis of functional neuroimaging data as such data are often singular. [3] It is possible to compute the regularized canonical vectors in the lower-dimensional space. [4]

  4. Canonical correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Canonical_correspondence...

    In multivariate analysis, canonical correspondence analysis (CCA) is an ordination technique that determines axes from the response data as a unimodal combination of measured predictors. CCA is commonly used in ecology in order to extract gradients that drive the composition of ecological communities.

  5. Origin (data analysis software) - Wikipedia

    en.wikipedia.org/wiki/Origin_(data_analysis...

    2020/4/30 Origin 2020b. Mini toolbar for worksheet & matrix, data connector navigator panel, browser graphs. Worksheet cells no longer showing ####. New Apps such as Canonical Correlation Analysis, Correlation plot etc. 2019/10/25 Origin 2020. Only provides 64 bit Origin & OriginPro. Mini toolbars, much faster import and plotting of large dataset.

  6. Generalized canonical correlation - Wikipedia

    en.wikipedia.org/wiki/Generalized_canonical...

    In statistics, the generalized canonical correlation analysis (gCCA), is a way of making sense of cross-correlation matrices between the sets of random variables when there are more than two sets. While a conventional CCA generalizes principal component analysis (PCA) to two sets of random variables, a gCCA generalizes PCA to more than two sets ...

  7. Canonical analysis - Wikipedia

    en.wikipedia.org/wiki/Canonical_analysis

    In statistics, canonical analysis (from Ancient Greek: κανων bar, measuring rod, ruler) belongs to the family of regression methods for data analysis. Regression analysis quantifies a relationship between a predictor variable and a criterion variable by the coefficient of correlation r, coefficient of determination r 2, and the standard regression coefficient β.

  8. Path analysis (statistics) - Wikipedia

    en.wikipedia.org/wiki/Path_analysis_(statistics)

    In statistics, path analysis is used to describe the directed dependencies among a set of variables. This includes models equivalent to any form of multiple regression analysis, factor analysis, canonical correlation analysis, discriminant analysis, as well as more general families of models in the multivariate analysis of variance and covariance analyses (MANOVA, ANOVA, ANCOVA).

  9. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram. The correlogram is a commonly used tool for checking randomness in a data set. If random, autocorrelations should be near zero for any and all time ...