ALGORITHM 587: Two Algorithms for the Linearly Constrained Least Squares Problem

ACM Transactions on Mathematical Software (TOMS)

Volumn 8, Issue 3, 1982, Pages 323-333

  Hanson, Richard J ^a   Haskell, Karen H ^a  

^a SANDIA NATIONAL LABORATORIES   (United States)

Author keywords

Additional Key Words and Phrases: linear least squares solution; covarmnce matrix; equality constraints; inconsistent constraints; inequality constraints; nonnegativity constraints

Indexed keywords

EID: 84976736914     PISSN: 00983500     EISSN: 15577295     Source Type: Journal    
DOI: 10.1145/356004.356010     Document Type: Article

References (9)

1. Pox, P.A., Hull, A.D., and Schryer, N.D. The PORT mathematical subroutine library. ACM Trans. Math. Softw. 4, 2 (June 1978), 104-126.
2. Hanson, R J Constrained Least Squares Curve Fitting to Discrete Data Using B-splmes-A User's Guide Available as Sandia National Laboratories Tech Rep. SAND78-1291, Sandia National Laboratomes, Albuquerque, N mex Feb 1971
3. Haskell, K.H., and Hanson, R J. An algorithm for linear least squares problems with equality and nonnegativity constraints Math Program. 21 (1981), 98-118.
4. Haskell, K.H., and Hanson, R.J. Selected algorithms for the linearly constrained least squares problem-A user's guide Tech Rep. SAND78-1290, Sandia National Laboratories, Albuquerque, N. Mex., 1979.
5. Jones, R.E. SLATEC common mathematical library error handling package. Tech. Rep. SAND78-1189, Sandia National Laboratories, Albuquerque, N 1978.
6. Lawson, C L. The Covariance Matrix for the Solution Vector of an Equality-Constrained Least-Squares Problem. Available as Jet Propulsion Laboratories Tech Memo 33-807, Jet Propulsion Laboratories, Pasadena, Calif., Dec. 1976.
7. Lawson, C L., and Hanson, R.J. Solving Least Squares Problems Prentice-Hall, Englewood Cliffs, N J, 1974.
8. Lawson, C L., Hanson, R.J., Kincaid, D.R., and Krogh, F.T. Basic linear algebra subprograms for Fortran usage ACM Trans. Math. Softw. 5, 3 (Sept. 1979), 308-323.
9. Wampler, R.H. Problems used in testing the efficiency and accuracy of the modified GramSchmidt least squares algorithm. NBS Tech. Note 1126, Aug. 1980.