Rank — the series
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Rank is a decision
A floating-point matrix does not have a rank. It has a spectrum of singular values, and somewhere in that spectrum is a place where the values stop being signal and start being noise. Deciding where is a judgement, and the evidence for it is a gap.
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The cheap rank and what it cannot see
Almost nobody computes singular values to decide a rank. The standard substitute is QR with column pivoting, read off the diagonal of R — and there is a triangular matrix on which the greedy rule makes no interchange at all, has no better column available at any step, and reports a matrix eight orders of magnitude further from singular than it is.
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A rank that depends on the thread count
One 60 × 14 matrix, one threshold, seven partitionings of the inner products that build its Gram matrix — and numerical ranks of 12, 12, 12, 10, 10, 11 and 11. Not a digit of an answer: the number of columns a model built from this matrix would have.
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A good curve and a bad verdict
The diagonal of a column-pivoted R is famous for the one matrix it is wrong about. On that matrix it is right about thirty-nine of its forty entries — every |rₖₖ| within a factor of six of the σₖ it stands for — and wrong by 4·10⁶ at the fortieth, which is the only one a rank verdict ever reads.