Hello,

I have a matrix with 267 columns, all rows of which have at least one
column missing (NA).
All three methods i've tried (pcs, princomp, and prcomp) fail with either

"Error in svd(zsmall) : infinite or missing values in 'x'" (latter two)

or

"Error in cov.wt(z) : 'x' must contain finite values only"

The last one happens because of the check

if (!all(is.finite(x)))

in cov.wt

Q: is there a way to do princomp or another method where every row has at
least one missing column?

I guess if missing values are thrown out, that leaves me with a zero row
matrix.
I could find the maximal set of columns such that there exists a subset of
rows with non NA values for every column in the set  - what is an efficient
way to do that?

Kind Regards
JS

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