Apply part (b) to the first column of , using the identity if it is already the zero vector. This gives an orthogonal matrix for which has zeros below its first diagonal entry. At stage , apply a Householder transformation to rows of column , and extend it by the identity on the first coordinates. If that trailing column is zero, again use the identity. The transformation preserves zeros in earlier columns, since their trailing entries already vanish.
After at most stages,
is an upper triangular matrix. Each is symmetric and orthogonal, so with
we have and
No invertibility assumption was used, so the Householder QR decomposition also exists for singular matrices.

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