The routine may be called by the names f02wuf or nagf_eigen_real_triang_svd.
3Description
The upper triangular matrix is factorized as
where and are orthogonal matrices and is an diagonal matrix with non-negative diagonal elements, , ordered such that
The columns of are the left-hand singular vectors of , the diagonal elements of are the singular values of and the columns of are the right-hand singular vectors of .
Either or both of and may be requested and the matrix given by
where is an given matrix, may also be requested.
The routine obtains the singular value decomposition by first reducing to bidiagonal form by means of Givens plane rotations and then using the algorithm to obtain the singular value decomposition of the bidiagonal form.
Note that if is any orthogonal diagonal matrix so that
(that is the diagonal elements of are or ) then
is also a singular value decomposition of .
4References
Chan T F (1982) An improved algorithm for computing the singular value decomposition ACM Trans. Math. Software8 72–83
Dongarra J J, Moler C B, Bunch J R and Stewart G W (1979) LINPACK Users' Guide SIAM, Philadelphia
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Hammarling S (1985) The singular value decomposition in multivariate statistics SIGNUM Newsl.20(3) 2–25
Wilkinson J H (1978) Singular Value Decomposition – Basic Aspects Numerical Software – Needs and Availability (ed D A H Jacobs) Academic Press
5Arguments
1: – IntegerInput
On entry: , the order of the matrix .
If , an immediate return is effected.
Constraint:
.
2: – Real (Kind=nag_wp) arrayInput/Output
Note: the second dimension of the array a
must be at least
.
On entry: the leading upper triangular part of the array a must contain the upper triangular matrix .
On exit: if , the part of a will contain the orthogonal matrix , otherwise the upper triangular part of a is used as internal workspace, but the strictly lower triangular part of a is not referenced.
3: – IntegerInput
On entry: the first dimension of the array a as declared in the (sub)program from which f02wuf is called.
Note: the second dimension of the array q
must be at least
if , and at least otherwise.
On exit: with , the leading part of the array q will contain the orthogonal matrix . Otherwise the array q is not referenced.
9: – IntegerInput
On entry: the first dimension of the array q as declared in the (sub)program from which f02wuf is called.
Constraints:
if , ;
otherwise .
10: – Real (Kind=nag_wp) arrayOutput
On exit:
If the array sv will contain the diagonal elements of the matrix.
If the array sv will contain the diagonal elements of the bidiagonal matrix in the factorization ; the superdiagonal elements of will be contained in the first elements of work.
11: – LogicalInput
On entry: must be .TRUE. if the matrix is required, in which case is overwritten on the array a, otherwise wantp must be .FALSE..
12: – Real (Kind=nag_wp) arrayOutput
Note: the dimension of the array work
must be at least
if and and , if ( and and ) or ( and ( or )), and at least otherwise.
On exit: contains the super-diagonal elements of the bidiagonal matrix computed during the bidiagonalization stage; contains the total number of iterations taken by the algorithm.
The rest of the array is used as internal workspace.
13: – IntegerInput/Output
On entry: ifail must be set to , or to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of means that an error message is printed while a value of means that it is not.
If halting is not appropriate, the value or is recommended. If message printing is undesirable, then the value is recommended. Otherwise, the value is recommended. When the value or is used it is essential to test the value of ifail on exit.
On exit: unless the routine detects an error or a warning has been flagged (see Section 6).
6Error Indicators and Warnings
If on entry or , explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
The algorithm has failed to converge. singular values have not been found.
On entry, and .
Constraint: .
On entry, , and .
Constraint: if , .
On entry, and .
Constraint: if , .
On entry, .
Constraint: .
On entry, .
Constraint: .
An unexpected error has been triggered by this routine. Please
contact NAG.
See Section 7 in the Introduction to the NAG Library FL Interface for further information.
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library FL Interface for further information.
Dynamic memory allocation failed.
See Section 9 in the Introduction to the NAG Library FL Interface for further information.
7Accuracy
The computed factors , and satisfy the relation
where
is the machine precision, is a modest function of and denotes the spectral (two) norm. Note that .
A similar result holds for the computed matrix .
The computed matrix satisfies the relation
where is exactly orthogonal and
where is a modest function of . A similar result holds for .
8Parallelism and Performance
f02wuf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f02wuf makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.
9Further Comments
For given values of ncolb, wantq and wantp, the number of floating-point operations required is approximately proportional to .
Following the use of this routine the rank of may be estimated by a call to f06klf. The statement
irank = f06klf(n,sv,1,tol)
returns the value in irank, where is the smallest integer for which , and is the tolerance supplied in tol, so that irank is an estimate of the rank of and thus also of . If tol is supplied as negative then the machine precision is used in place of tol.
10Example
This example finds the singular value decomposition of the upper triangular matrix