Hi,

I have written small code in C++ using Armadillo and inline with
RcppArmadillo package.
The input is data.marix(X). Some cells might be NAs. Example in R: X =
matrix(sample(c(rnorm(10*9.9),NA)),ncol=10)

I am calculating conditional correlation on columns of that matrix, just
picking vectors, so cor(X,Y).
The problem is that sometimes I might have empty cell in one or both
vectors, in that case I would like to skip that row, and procede with
calculating Pearson's correlation on remaining data. I know that there will
be difference in degrees of freedom, but I have over 100 rows, so skiping
few shouldnt matter that much.

Basically my question boils down to solving the problem:
How to find which colvec cells are nan, and remove this index from both X
and Y colvec, before calculating correlation.

I would be very grateful for help,

Kind regards,
Mateusz Kaduk
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