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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