Abramowitz, M., and Stegun, I. A., eds. (1972). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. 10th printing. New York: Dover.
Al-Baali, M., and Fletcher, R. (1985). “Variational Methods for Nonlinear Least Squares.” Journal of the Operations Research Society 36:405–421.
Al-Baali, M., and Fletcher, R. (1986). “An Efficient Line Search for Nonlinear Least Squares.” Journal of Optimization Theory and Applications 48:359–377.
Anderson, B. D., and Moore, J. B. (1979). Optimal Filtering. Englewood Cliffs, NJ: Prentice-Hall.
Bard, Y. (1974). Nonlinear Parameter Estimation. New York: Academic Press.
Bates, D. M., and Watts, D. G. (1988). Nonlinear Regression Analysis and Its Applications. New York: John Wiley & Sons.
Beale, E. M. L. (1972). “A Derivation of Conjugate Gradients.” In Numerical Methods for Nonlinear Optimization, edited by F. A. Lootsma, 39–43. London: Academic Press.
Betts, J. T. (1977). “An Accelerated Multiplier Method for Nonlinear Programming.” Journal of Optimization Theory and Applications 21:137–174.
Bracken, J., and McCormick, G. P. (1968). Selected Applications of Nonlinear Programming. New York: John Wiley & Sons.
Chamberlain, R. M., Powell, M. J. D., Lemarechal, C., and Pedersen, H. C. (1982). “The Watchdog Technique for Forcing Convergence in Algorithms for Constrained Optimization.” Mathematical Programming 16:1–17.
De Jong, P. (1988). “The Likelihood for a State Space Model.” Biometrika 75:165–169.
Dennis, J. E., Gay, D. M., and Welsch, R. E. (1981). “An Adaptive Nonlinear Least-Squares Algorithm.” ACM Transactions on Mathematical Software 7:348–368.
Dennis, J. E., and Mei, H. H. W. (1979). “Two New Unconstrained Optimization Algorithms Which Use Function and Gradient Values.” Journal of Optimization Theory and Applications 28:453–482.
Dennis, J. E., and Schnabel, R. B. (1983). Numerical Methods for Unconstrained Optimization and Nonlinear Equations. Englewood Cliffs, NJ: Prentice-Hall.
Eskow, E., and Schnabel, R. B. (1991). “Algorithm 695: Software for a New Modified Cholesky Factorization.” ACM Transactions on Mathematical Software 17:306–312.
Fletcher, R. (1987). Practical Methods of Optimization. 2nd ed. Chichester, UK: John Wiley & Sons.
Fletcher, R., and Powell, M. J. D. (1963). “A Rapidly Convergent Descent Method for Minimization.” Computer Journal 6:163–168.
Fletcher, R., and Xu, C. (1987). “Hybrid Methods for Nonlinear Least Squares.” Journal of Numerical Analysis 7:371–389.
Gay, D. M. (1983). “Subroutines for Unconstrained Minimization.” ACM Transactions on Mathematical Software 9:503–524.
George, J. A., and Liu, J. W. (1981). Computer Solutions of Large Sparse Positive Definite Systems. Englewood Cliffs, NJ: Prentice-Hall.
Gill, P. E., Murray, W., Saunders, M. A., and Wright, M. H. (1983). “Computing Forward-Difference Intervals for Numerical Optimization.” SIAM Journal on Scientific and Statistical Computing 4:310–321.
Gill, P. E., Murray, W., Saunders, M. A., and Wright, M. H. (1984). “Procedures for Optimization Problems with a Mixture of Bounds and General Linear Constraints.” ACM Transactions on Mathematical Software 10:282–298.
Gill, P. E., Murray, W., and Wright, M. H. (1981). Practical Optimization. New York: Academic Press.
Goldfeld, S. M., Quandt, R. E., and Trotter, H. F. (1966). “Maximisation by Quadratic Hill-Climbing.” Econometrica 34:541–551.
Hartmann, W. M. (1991). The NLP Procedure: Extended User’s Guide, Releases 6.08 and 6.10. Cary, NC: SAS Institute Inc.
Hock, W., and Schittkowski, K. (1981). Test Examples for Nonlinear Programming Codes. Vol. 187 of Lecture Notes in Economics and Mathematical Systems. Berlin: Springer-Verlag.
Jennrich, R. I., and Sampson, P. F. (1968). “Application of Stepwise Regression to Nonlinear Estimation.” Technometrics 10:63–72.
Lawless, J. F. (1982). Statistical Methods and Methods for Lifetime Data. New York: John Wiley & Sons.
Liebman, J., Lasdon, L., Schrage, L., and Waren, A. (1986). Modeling and Optimization with GINO. Redwood City, CA: Scientific Press.
Lindström, P., and Wedin, P. A. (1984). “A New Line-Search Algorithm for Nonlinear Least-Squares Problems.” Mathematical Programming 29:268–296.
Lütkepohl, H. (1991). Introduction to Multiple Time Series Analysis. Berlin: Springer-Verlag.
Moré, J. J. (1978). “The Levenberg-Marquardt Algorithm: Implementation and Theory.” In Lecture Notes in Mathematics, vol. 30, edited by G. A. Watson, 105–116. Berlin: Springer-Verlag.
Moré, J. J., Garbow, B. S., and Hillstrom, K. E. (1981). “Testing Unconstrained Optimization Software.” ACM Transactions on Mathematical Software 7:17–41.
Moré, J. J., and Sorensen, D. C. (1983). “Computing a Trust-Region Step.” SIAM Journal on Scientific and Statistical Computing 4:553–572.
Moré, J. J., and Wright, S. J. (1993). Optimization Software Guide. Philadelphia: SIAM.
Murtagh, B. A., and Saunders, M. A. (1983). MINOS 5.0 User’s Guide. Technical Report SOL 83-20, Stanford University.
Nelder, J. A., and Mead, R. (1965). “A Simplex Method for Function Minimization.” Computer Journal 7:308–313.
Peto, R. (1973). “Experimental Survival Curves for Interval-Censored Data.” Journal of the Royal Statistical Society, Series C 22:86–91.
Polak, E. (1971). Computational Methods in Optimization. New York: Academic Press.
Powell, M. J. D. (1977). “Restart Procedures for the Conjugate Gradient Method.” Mathematical Programming 12:241–254.
Powell, M. J. D. (1978a). “Algorithms for Nonlinear Constraints That Use Lagrangian Functions.” Mathematical Programming 14:224–248.
Powell, M. J. D. (1978b). “A Fast Algorithm for Nonlinearly Constrained Optimization Calculations.” In Lecture Notes in Mathematics, vol. 630, edited by G. A. Watson, 144–175. Berlin: Springer-Verlag.
Powell, M. J. D. (1982a). “Extensions to Subroutine VF02AD.” In Systems Modeling and Optimization, Lecture Notes in Control and Information Sciences, vol. 38, edited by R. F. Drenick, and F. Kozin, 529–538. Berlin: Springer-Verlag.
Powell, M. J. D. (1982b). VMCWD: A Fortran Subroutine for Constrained Optimization. Technical Report DAMTP 1982/NA4, Department of Applied Mathematics and Theoretical Physics, University of Cambridge.
Powell, M. J. D. (1992). A Direct Search Optimization Method That Models the Objective and Constraint Functions by Linear Interpolation. Technical Report DAMTP 1992/NA5, Department of Applied Mathematics and Theoretical Physics, University of Cambridge.
Rosenbrock, H. H. (1960). “An Automatic Method for Finding the Greatest or Least Value of a Function.” Computer Journal 3:175–184.
Schittkowski, K. (1978). “An Adaptive Precision Method for the Numerical Solution of Constrained Optimization Problems Applied to a Time-Optimal Heating Process.” In Optimization Techniques: Proceedings of the Eighth IFIP Conference on Optimization Techniques. Berlin: Springer-Verlag.
Schittkowski, K. (1987). More Test Examples for Nonlinear Programming Codes. Vol. 282 of Lecture Notes in Economics and Mathematical Systems. Berlin: Springer-Verlag.
Schittkowski, K., and Stoer, J. (1979). “A Factorization Method for the Solution of Constrained Linear Least Squares Problems Allowing Subsequent Data Changes.” Numerische Mathematik 31:431–463.
Turnbull, B. W. (1976). “The Empirical Distribution Function with Arbitrarily Grouped, Censored, and Truncated Data.” Journal of the Royal Statistical Society, Series B 38:290–295.
Venzon, D. J., and Moolgavkar, S. H. (1988). “A Method for Computing Profile-Likelihood-Based Confidence Intervals.” Journal of the Royal Statistical Society, Series C 37:87–94.
Wedin, P. A., and Lindström, P. (1987). Methods and Software for Nonlinear Least Squares Problems. Technical Report No. UMINF 133.87, Umeå University, Sweden.
Ziegel, E. R., and Gorman, J. W. (1980). “Kinetic Modelling with Multipurpose Data.” Technometrics 27:352–357.