I am using the `fit(CCA,...)`

function from the `MultivariateStats.jl`

package and I want to know how to pull out the principal canonical vectors. The resulting `CCA`

model object has methods like `xprojection`

and `yprojection`

which respectively give you the projection matrices that map the two random variables (the inputs `X`

and `Y`

) into their common, correlation-maximizing subspace. But I don’t know how to simply extract the canonical vectors for each variable themselves, because I’m not familiar enough with the maths behind CCA/CVA to know how to compute them using the projection matrices and/or the ‘mean vectors’ (which is another provided method of the `CCA`

object).

Just wondering if you ever worked out how to do this, or found good examples/documentation outside of the readthedocs page?