statsmodels.multivariate.cancorr.CanCorr¶
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class
statsmodels.multivariate.cancorr.
CanCorr
(endog, exog, tolerance=1e-08, missing='none', hasconst=None, **kwargs)[source]¶ Canonical correlation analysis using singluar value decomposition
For matrices exog=x and endog=y, find projections x_cancoef and y_cancoef such that:
x1 = x * x_cancoef, x1’ * x1 is identity matrix y1 = y * y_cancoef, y1’ * y1 is identity matrixand the correlation between x1 and y1 is maximized.
References
[*] http://numerical.recipes/whp/notes/CanonCorrBySVD.pdf [†] http://www.csun.edu/~ata20315/psy524/docs/Psy524%20Lecture%208%20CC.pdf [‡] http://www.mathematica-journal.com/2014/06/canonical-correlation-analysis/ Attributes
endog (array) See Parameters. exog (array) See Parameters. cancorr (array) The canonical correlation values y_cancoeff: array The canonical coeefficients for endog x_cancoeff: array The canonical coefficients for exog Methods
corr_test
()Approximate F test Perform multivariate statistical tests of the hypothesis that there is no canonical correlation between endog and exog. fit
()Fit a model to data. from_formula
(formula, data[, subset, drop_cols])Create a Model from a formula and dataframe. predict
(params[, exog])After a model has been fit predict returns the fitted values.