Applies back multiplying factors in solving the least squares problem using divide and conquer SVD approach. Used by
The routine applies back the multiplying factors of either the left or right singular vector matrix of a diagonal matrix appended by a row to the right hand side matrix
Bin solving the least squares problem using the divide-and-conquer SVD approach.
For the left singular vector matrix, three types of orthogonal matrices are involved:
(1L) Givens rotations: the number of such rotations is
givptr;the pairs of columns/rows they were applied to are stored in
s-values of these rotations are stored in
(2L) Permutation. The (
nl+1)-st row of
Bis to be moved to the first row, and for j=2:
j)-th row of
Bis to be moved to the
(3L) The left singular vector matrix of the remaining matrix.
For the right singular vector matrix, four types of orthogonal matrices are involved:
(1R) The right singular vector matrix of the remaining matrix.
, one extra Givens rotation to generate the right null space.
(3R) The inverse transformation of (2L).
(4R) The inverse transformation of (1L).
- INTEGER. Specifies whether singular vectors are to be computed in factored form:If: Left singular vector matrix.icompq= 0If: Right singular vector matrix.icompq= 1
- INTEGER. The row dimensio