Page 279 - Compact Numerical Methods For Computers
P. 279
266 Compact numerical methods for computers
HADLEY G 1962 Linear Programming (Reading, MA: Addison-Wesley)
HAMMARLING S 1974 A note on modifications to the Givens’ plane rotation J. Inst. Maths Applics 13
215-18
HARTLEY H O 1948 The estimation of nonlinear parameters by ‘internal least squares’ Biometrika 35 32-45
----1961 The modified Gauss-Newton method for the fitting of non-linear regression functions by least
squares Technometrics 3 269-80
HARTLEY H O and BOOKER A 1965 Nonlinear least squares estimation Ann. Math. Stat. 36 638-50
HEALY M J R 1968 Triangular decomposition of a symmetric matrix (algorithm AS6) Appl Srat. 17 195- 7
HENRICI P 1964 Elements of Numerical Analysis (New York: Wiley)
HESTENES M R 1958 Inversion of matrices by biorthogonahzation and related results J. Soc. Ind. Appl.
Math. 5 51-90
---1975 Pseudoinverses and conjugate gradients Commun. ACM 18 40-3
HESTENES M R and STIFFEL E 1952 Methods of conjugate gradients for solving linear systems J. Res. Nat.
Bur. Stand. 49 409-36
HILLSTROM K E 1976 A simulation test approach to the evaluation and comparison of unconstrained
nonlinear optimization algorithms Argonne National Laboratory Report ANL-76-20
HOCK W and SCHITTKOWSKI K 1981 Test examples for nonlinear programming codes Lecture Notes in
Economics and Mathematical Systems 187 (Berlin: Springer)
HOLT J N and FLETCHER R 1979 An algorithm for constrained nonlinear least squares J. Inst. Maths
Applics 23 449-63
HOOKE R and JEEVES T A 1961 ‘Direct Search’ solution of numerical and statistical problems J. ACM 8
212-29
JACOBI C G J 1846 Uber ein leichtes Verfahren. die in der Theorie der Sakularstorungen vorkommenden
Gleichungen numerisch aufzulosen Crelle's J. 30 51-94
JACOBY S L S. KOWALIK J S and PIZZO J T 1972 Iterative Methods for Nonlinear Optimization Problems
(Englewood Cliff‘s, NJ: Prentice Hall)
JENKINS M A and TRAUB J F 1975 Principles for testing polynomial zero-finding programs ACM Trans.
Math. Softw. 1 26-34
JONES A 1970 Spiral a new algorithm for non-linear parameter estimation using least squares Comput. J.
13 301-8
KAHANER D, MOLER C and NASH S G 1989 Numerical Analysis and Software (Englewood Cliffs. NJ:
Prentice Hall)
KAHANER D and PARLETT B N 1976 How far should you go with the Lanczos process’! Sparse Matrix
Computations eds J R Bunch and D J Rose (New York: Academic) pp 131-44
KAISER H F 1972 The JK method: a procedure for finding the eigenvectors and eigenvalues of a real
symmetric matrix Comput. J. 15 271-3
KARMARKAR N 1984 A new polynomial time algorithm for linear programming Combinatorica 4 373-95
KARPINSKI R 1985 PARANOIA: a floating-point benchmark Byte 10(2) 223-35 (February)
KAUFMAN L 1975 A variable projection method for solving separable nonlinear least squares problems
BIT 15 49-57
KENDALL M G 1973 Time-series (London: Griffin)
KENDALL M G and STEWART A 1958-66 The Advanced Theory of Statistics vols 1-3 (London: Griffin)
KENNEDY W J Jr and GENTLE J E 1980 Statistical Computing (New York: Marcel Dekker)
KERNIGHAN B W and PLAUGER P J 1974 The Elements of Programming Style (New York: McGraw-Hill)
KIRKPATRICK S, GELATT C D Jr and VECCHI M P 1983 Optimization by simulated annealing Science 220
(4598) 671-80
KOWALIK J and OSBORNE M R 1968 Methods for Unconstrained Optimization Problems (New York:
American Elsevier)
KUESTER J L and MIZE H H 1973 Optimization Techniques with FORTRAN (New York London Toronto:
McGraw-Hill)
KUI.ISCH U 1987 Pascal SC: A Pascal extension for scientific computation (Stuttgart: B G Teubner and
Chichester: Wiley)
LANCZOS C 1956 Applied Analysis (Englewood Cliffs. NJ: Prentice Hall)
LAWSON C L and HANSON R J 1974 Solving Least Squares Problems (Englewood Cliffs, NJ: Prentice Hall)
LEVENBERG K 1944 A method for the solution of certain non-linear problems in least squares Q. Appl.
Math. 2 164-8