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- *DECK EISDOC
- SUBROUTINE EISDOC
- C***BEGIN PROLOGUE EISDOC
- C***PURPOSE Documentation for EISPACK, a collection of subprograms for
- C solving matrix eigen-problems.
- C***LIBRARY SLATEC (EISPACK)
- C***CATEGORY D4, Z
- C***TYPE ALL (EISDOC-A)
- C***KEYWORDS EIGENVALUES, EIGENVECTORS, EISPACK
- C***AUTHOR Vandevender, W. H., (SNLA)
- C***DESCRIPTION
- C
- C **********EISPACK Routines**********
- C
- C single double complx
- C ------ ------ ------
- C
- C RS - CH Computes eigenvalues and, optionally,
- C eigenvectors of real symmetric
- C (complex Hermitian) matrix.
- C
- C RSP - - Compute eigenvalues and, optionally,
- C eigenvectors of real symmetric matrix
- C packed into a one dimensional array.
- C
- C RG - CG Computes eigenvalues and, optionally,
- C eigenvectors of a real (complex) general
- C matrix.
- C
- C BISECT - - Compute eigenvalues of symmetric tridiagonal
- C matrix given interval using Sturm sequencing.
- C
- C IMTQL1 - - Computes eigenvalues of symmetric tridiagonal
- C matrix implicit QL method.
- C
- C IMTQL2 - - Computes eigenvalues and eigenvectors of
- C symmetric tridiagonal matrix using
- C implicit QL method.
- C
- C IMTQLV - - Computes eigenvalues of symmetric tridiagonal
- C matrix by the implicit QL method.
- C Eigenvectors may be computed later.
- C
- C RATQR - - Computes largest or smallest eigenvalues
- C of symmetric tridiagonal matrix using
- C rational QR method with Newton correction.
- C
- C RST - - Compute eigenvalues and, optionally,
- C eigenvectors of real symmetric tridiagonal
- C matrix.
- C
- C RT - - Compute eigenvalues and eigenvectors of
- C a special real tridiagonal matrix.
- C
- C TQL1 - - Compute eigenvalues of symmetric tridiagonal
- C matrix by QL method.
- C
- C TQL2 - - Compute eigenvalues and eigenvectors
- C of symmetric tridiagonal matrix.
- C
- C TQLRAT - - Computes eigenvalues of symmetric
- C tridiagonal matrix a rational variant
- C of the QL method.
- C
- C TRIDIB - - Computes eigenvalues of symmetric
- C tridiagonal matrix given interval using
- C Sturm sequencing.
- C
- C TSTURM - - Computes eigenvalues of symmetric tridiagonal
- C matrix given interval and eigenvectors
- C by Sturm sequencing. This subroutine
- C is a translation of the ALGOL procedure
- C TRISTURM by Peters and Wilkinson. HANDBOOK
- C FOR AUTO. COMP., VOL.II-LINEAR ALGEBRA,
- C 418-439(1971).
- C
- C BQR - - Computes some of the eigenvalues of a real
- C symmetric matrix using the QR method with
- C shifts of origin.
- C
- C RSB - - Computes eigenvalues and, optionally,
- C eigenvectors of symmetric band matrix.
- C
- C RSG - - Computes eigenvalues and, optionally,
- C eigenvectors of symmetric generalized
- C eigenproblem: A*X=(LAMBDA)*B*X
- C
- C RSGAB - - Computes eigenvalues and, optionally,
- C eigenvectors of symmetric generalized
- C eigenproblem: A*B*X=(LAMBDA)*X
- C
- C RSGBA - - Computes eigenvalues and, optionally,
- C eigenvectors of symmetric generalized
- C eigenproblem: B*A*X=(LAMBDA)*X
- C
- C RGG - - Computes eigenvalues and eigenvectors
- C for real generalized eigenproblem:
- C A*X=(LAMBDA)*B*X.
- C
- C BALANC - CBAL Balances a general real (complex)
- C matrix and isolates eigenvalues whenever
- C possible.
- C
- C BANDR - - Reduces real symmetric band matrix
- C to symmetric tridiagonal matrix and,
- C optionally, accumulates orthogonal similarity
- C transformations.
- C
- C HTRID3 - - Reduces complex Hermitian (packed) matrix
- C to real symmetric tridiagonal matrix by unitary
- C similarity transformations.
- C
- C HTRIDI - - Reduces complex Hermitian matrix to real
- C symmetric tridiagonal matrix using unitary
- C similarity transformations.
- C
- C TRED1 - - Reduce real symmetric matrix to symmetric
- C tridiagonal matrix using orthogonal
- C similarity transformations.
- C
- C TRED2 - - Reduce real symmetric matrix to symmetric
- C tridiagonal matrix using and accumulating
- C orthogonal transformations.
- C
- C TRED3 - - Reduce symmetric matrix stored in packed
- C form to symmetric tridiagonal matrix using
- C orthogonal transformations.
- C
- C ELMHES - COMHES Reduces real (complex) general matrix to
- C upper Hessenberg form using stabilized
- C elementary similarity transformations.
- C
- C ORTHES - CORTH Reduces real (complex) general matrix to upper
- C Hessenberg form orthogonal (unitary)
- C similarity transformations.
- C
- C QZHES - - The first step of the QZ algorithm for solving
- C generalized matrix eigenproblems. Accepts
- C a pair of real general matrices and reduces
- C one of them to upper Hessenberg and the other
- C to upper triangular form using orthogonal
- C transformations. Usually followed by QZIT,
- C QZVAL, QZ
- C
- C QZIT - - The second step of the QZ algorithm for
- C generalized eigenproblems. Accepts an upper
- C Hessenberg and an upper triangular matrix
- C and reduces the former to quasi-triangular
- C form while preserving the form of the latter.
- C Usually preceded by QZHES and followed by QZVAL
- C and QZVEC.
- C
- C FIGI - - Transforms certain real non-symmetric
- C tridiagonal matrix to symmetric tridiagonal
- C matrix.
- C
- C FIGI2 - - Transforms certain real non-symmetric
- C tridiagonal matrix to symmetric tridiagonal
- C matrix.
- C
- C REDUC - - Reduces generalized symmetric eigenproblem
- C A*X=(LAMBDA)*B*X, to standard symmetric
- C eigenproblem using Cholesky factorization.
- C
- C REDUC2 - - Reduces certain generalized symmetric
- C eigenproblems standard symmetric eigenproblem,
- C using Cholesky factorization.
- C
- C - - COMLR Computes eigenvalues of a complex upper
- C Hessenberg matrix using the modified LR method.
- C
- C - - COMLR2 Computes eigenvalues and eigenvectors of
- C complex upper Hessenberg matrix using
- C modified LR method.
- C
- C HQR - COMQR Computes eigenvalues of a real (complex)
- C upper Hessenberg matrix using the QR method.
- C
- C HQR2 - COMQR2 Computes eigenvalues and eigenvectors of
- C real (complex) upper Hessenberg matrix
- C using QR method.
- C
- C INVIT - CINVIT Computes eigenvectors of real (complex)
- C Hessenberg matrix associated with specified
- C eigenvalues by inverse iteration.
- C
- C QZVAL - - The third step of the QZ algorithm for
- C generalized eigenproblems. Accepts a pair
- C of real matrices, one quasi-triangular form
- C and the other in upper triangular form and
- C computes the eigenvalues of the associated
- C eigenproblem. Usually preceded by QZHES,
- C QZIT, and followed by QZVEC.
- C
- C BANDV - - Forms eigenvectors of real symmetric band
- C matrix associated with a set of ordered
- C approximate eigenvalue by inverse iteration.
- C
- C QZVEC - - The optional fourth step of the QZ algorithm
- C for generalized eigenproblems. Accepts
- C a matrix in quasi-triangular form and another
- C in upper triangular and computes the
- C eigenvectors of the triangular problem
- C and transforms them back to the original
- C coordinates Usually preceded by QZHES, QZIT,
- C QZVAL.
- C
- C TINVIT - - Eigenvectors of symmetric tridiagonal
- C matrix corresponding to some specified
- C eigenvalues, using inverse iteration.
- C
- C BAKVEC - - Forms eigenvectors of certain real
- C non-symmetric tridiagonal matrix from
- C symmetric tridiagonal matrix output from FIGI.
- C
- C BALBAK - CBABK2 Forms eigenvectors of real (complex) general
- C matrix from eigenvectors of matrix output
- C from BALANC (CBAL).
- C
- C ELMBAK - COMBAK Forms eigenvectors of real (complex) general
- C matrix from eigenvectors of upper Hessenberg
- C matrix output from ELMHES (COMHES).
- C
- C ELTRAN - - Accumulates the stabilized elementary
- C similarity transformations used in the
- C reduction of a real general matrix to upper
- C Hessenberg form by ELMHES.
- C
- C HTRIB3 - - Computes eigenvectors of complex Hermitian
- C matrix from eigenvectors of real symmetric
- C tridiagonal matrix output from HTRID3.
- C
- C HTRIBK - - Forms eigenvectors of complex Hermitian
- C matrix from eigenvectors of real symmetric
- C tridiagonal matrix output from HTRIDI.
- C
- C ORTBAK - CORTB Forms eigenvectors of general real (complex)
- C matrix from eigenvectors of upper Hessenberg
- C matrix output from ORTHES (CORTH).
- C
- C ORTRAN - - Accumulates orthogonal similarity
- C transformations in reduction of real general
- C matrix by ORTHES.
- C
- C REBAK - - Forms eigenvectors of generalized symmetric
- C eigensystem from eigenvectors of derived
- C matrix output from REDUC or REDUC2.
- C
- C REBAKB - - Forms eigenvectors of generalized symmetric
- C eigensystem from eigenvectors of derived
- C matrix output from REDUC2
- C
- C TRBAK1 - - Forms the eigenvectors of real symmetric
- C matrix from eigenvectors of symmetric
- C tridiagonal matrix formed by TRED1.
- C
- C TRBAK3 - - Forms eigenvectors of real symmetric matrix
- C from the eigenvectors of symmetric tridiagonal
- C matrix formed by TRED3.
- C
- C MINFIT - - Compute Singular Value Decomposition
- C of rectangular matrix and solve related
- C Linear Least Squares problem.
- C
- C***REFERENCES B. T. Smith, J. M. Boyle, J. J. Dongarra, B. S. Garbow,
- C Y. Ikebe, V. C. Klema and C. B. Moler, Matrix Eigen-
- C system Routines - EISPACK Guide, Springer-Verlag,
- C 1976.
- C***ROUTINES CALLED (NONE)
- C***REVISION HISTORY (YYMMDD)
- C 811101 DATE WRITTEN
- C 861211 REVISION DATE from Version 3.2
- C 891214 Prologue converted to Version 4.0 format. (BAB)
- C 900723 PURPOSE section revised. (WRB)
- C 920501 Reformatted the REFERENCES section. (WRB)
- C***END PROLOGUE EISDOC
- C***FIRST EXECUTABLE STATEMENT EISDOC
- RETURN
- END
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