statsmodels.stats.multivariate_tools.CCStatsResult#

class statsmodels.stats.multivariate_tools.CCStatsResult(ccorr, eigenvalues, pillai_trace, wilks_lambda, hotelling_trace, roys_largest_root, df_resid, df_model)[source]#

Result of cc_stats.

Only returned if return_object=True is used, otherwise cc_stats returns the equivalent legacy dict.

Parameters:

ccorrndarray, 1-D: Canonical correlation coefficients, sorted from largest to smallest.
eigenvaluesndarray, 1-D: Eigenvalues corresponding to ccorr ** 2 / (1 - ccorr ** 2).
pillai_tracefloat: Pillai’s Trace statistic.
wilks_lambdafloat: Wilk’s Lambda statistic.
hotelling_tracefloat: Hotelling’s Trace statistic.
roys_largest_rootfloat: Roy’s Largest Root statistic.
df_residfloat: Residual degrees of freedom.
df_modelfloat: Model (hypothesis) degrees of freedom.

Attributes:

ccorr
df_model
df_resid
eigenvalues
hotelling_trace
pillai_trace
roys_largest_root
wilks_lambda

Methods

Properties

`ccorr`
`eigenvalues`
`pillai_trace`
`wilks_lambda`
`hotelling_trace`
`roys_largest_root`
`df_resid`
`df_model`