Visible to Intel only — GUID: GUID-99719D94-02B6-402C-A5C5-F83867776CDC
Visible to Intel only — GUID: GUID-99719D94-02B6-402C-A5C5-F83867776CDC
?gelss
Computes the minimum-norm solution to a linear least squares problem using the singular value decomposition of A.
Syntax
lapack_int LAPACKE_sgelss( int matrix_layout, lapack_int m, lapack_int n, lapack_int nrhs, float* a, lapack_int lda, float* b, lapack_int ldb, float* s, float rcond, lapack_int* rank );
lapack_int LAPACKE_dgelss( int matrix_layout, lapack_int m, lapack_int n, lapack_int nrhs, double* a, lapack_int lda, double* b, lapack_int ldb, double* s, double rcond, lapack_int* rank );
lapack_int LAPACKE_cgelss( int matrix_layout, lapack_int m, lapack_int n, lapack_int nrhs, lapack_complex_float* a, lapack_int lda, lapack_complex_float* b, lapack_int ldb, float* s, float rcond, lapack_int* rank );
lapack_int LAPACKE_zgelss( int matrix_layout, lapack_int m, lapack_int n, lapack_int nrhs, lapack_complex_double* a, lapack_int lda, lapack_complex_double* b, lapack_int ldb, double* s, double rcond, lapack_int* rank );
Include Files
- mkl.h
Description
The routine computes the minimum norm solution to a real linear least squares problem:
minimize ||b - A*x||2
using the singular value decomposition (SVD) of A. A is an m-by-n matrix which may be rank-deficient. Several right hand side vectors b and solution vectors x can be handled in a single call; they are stored as the columns of the m-by-nrhs right hand side matrix B and the n-by-nrhs solution matrix X. The effective rank of A is determined by treating as zero those singular values which are less than rcond times the largest singular value.
Input Parameters
- matrix_layout
-
Specifies whether matrix storage layout is row major (LAPACK_ROW_MAJOR) or column major (LAPACK_COL_MAJOR).
- m
-
The number of rows of the matrix A (m≥ 0).
- n
-
The number of columns of the matrix A
(n≥ 0).
- nrhs
-
The number of right-hand sides; the number of columns in B
(nrhs≥ 0).
- a, b
-
Arrays:
a(size max(1, lda*n) for column major layout and max(1, lda*m) for row major layout) contains the m-by-n matrix A.
b(size max(1, ldb*nrhs) for column major layout and max(1, ldb*max(m, n)) for row major layout) contains the m-by-nrhs right hand side matrix B.
- lda
-
The leading dimension of a; at least max(1, m)for column major layout and max(1, n) for row major layout.
- ldb
-
The leading dimension of b; must be at least max(1, m, n) for column major layout and at least max(1, nrhs) for row major layout.
- rcond
-
rcond is used to determine the effective rank of A. Singular values s(i) ≤rcond *s(1) are treated as zero.
If rcond <0, machine precision is used instead.
Output Parameters
- a
-
On exit, the first min(m, n) rows of a are overwritten with the matrix of right singular vectors of A, stored row-wise.
- b
-
Overwritten by the n-by-nrhs solution matrix X.
If m≥n and rank = n, the residual sum-of-squares for the solution in the i-th column is given by the sum of squares of modulus of elements n+1:m in that column.
- s
-
Array, size at least max(1, min(m, n)). The singular values of A in decreasing order. The condition number of A in the 2-norm is
k2(A) = s(1)/ s(min(m, n)) .
- rank
-
The effective rank of A, that is, the number of singular values which are greater than rcond *s(1).
Return Values
This function returns a value info.
If info=0, the execution is successful.
If info = -i, the i-th parameter had an illegal value.
If info = i, then the algorithm for computing the SVD failed to converge; i indicates the number of off-diagonal elements of an intermediate bidiagonal form which did not converge to zero.