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Second order sensitivity analysis and asymptotic theory of parametrized nonlinear programs

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Abstract

In this paper we study second-order differential properties of an optimal-value functionϕ(x). It is shown that under certain conditionsϕ(x) possesses second-order directional derivatives, which can be calculated by solving corresponding quadratic programs. Also upper and lower bounds on these derivatives are introduced under weaker assumptions. In particular we show that the second-order directional derivative is infinite if the corresponding quadratic program is unbounded. Finally sensitivity results are applied to investigate asymptotics of estimators in parametrized nonlinear programs.

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References

  1. R. Bellman,Introduction to matrix analysis (McGraw-Hill, New York, 1960).

    Google Scholar 

  2. J.H. Bigelow and N.Z. Shapiro, “Implicit function theorems for mathematical programming and for systems of inequalities”,Mathematical Programming 6 (1974) 141–156.

    Google Scholar 

  3. J.M. Danskin,The theory of max-min and its applications to weapons allocation problems, (Springer-Verlag, New York, 1967).

    Google Scholar 

  4. J. Dupačová, “Stability in stochastic programming with recourse-estimated parameters”,Mathematical Programming 28 (1984) 72–83.

    Google Scholar 

  5. A.V. Fiacco and G.P. McCormick,Nonlinear programming: Sequential unconstrained minimization techniques (Wiley, New York, 1968).

    Google Scholar 

  6. A.V. Fiacco, “Sensitivity analysis for nonlinear programming using penalty methods”,Mathematical Programming 10 (1976) 287–311.

    Google Scholar 

  7. A.V. Fiacco,Introduction to sensitivity and stability analysis in nonlinear programming (Academic Press, New York, 1983).

    Google Scholar 

  8. J. Gauvin and F. Dubeau, “Differential properties of the marginal functions in mathematical programming”,Mathematical Programming Study 19 (1982) 101–119.

    Google Scholar 

  9. B. Gollan, “On the marginal function in nonlinear programming”,Mathematics of Operations Research 9 (1984) 208–221.

    Google Scholar 

  10. K. Jittorntrum, “Solution point differentiability without strict complementarity in nonlinear programming”,Mathematical Programming Study 21 (1984) 127–138.

    Google Scholar 

  11. O.L. Mangasarian and S. Fromovitz, “The Fritz John necessary optimality conditions in the presence of equality and inequality constraints”,Journal of Mathematical Analysis and Applications 17 (1967) 37–47.

    Google Scholar 

  12. R.M. Pringle and A.A. Rayner,Generalized inverse matrices with applications to statistics, Griffin Statistical Monograph Series, London, 1971.

    Google Scholar 

  13. C.R. Rao,Linear statistical inference and its applications (Wiley, New York, 1973).

    Google Scholar 

  14. S.M. Robinson, “Perturbed Kuhn—Tucker points and rates of convergence for a class of nonlinearprogramming algorithms”,Mathematical Programming 7 (1974) 1–16.

    Google Scholar 

  15. S.M. Robinson, “Strongly regular generalized equations”,Mathematics of Operations Research 5 (1980) 43–62.

    Google Scholar 

  16. S.M. Robinson, “Generalized equations and their solutions, Part II: Applications to nonlinear programming”,Mathematical Programming Study 19 (1982) 200–221.

    Google Scholar 

  17. R.T. Rockafellar, “Generalized subgradients in mathematical programming”, in: A. Bachem, M. Grötschel and B. Korte, eds.,Mathematical programming, The state of the art (Springer-Verlag, Berlin, 1983).

    Google Scholar 

  18. R.T. Rockafellar, “Marginal values and second-order necessary conditions for optimality”,Mathematical Programming 26 (1983) 245–286.

    Google Scholar 

  19. A. Shapiro, “Asymptotic distribution theory in the analysis of covariance structures (a unified approach)”,South African Statistical Journal 17 (1983) 33–81.

    Google Scholar 

  20. A. Shapiro, “Second order derivatives of extremal-value functions and optimality conditions for semi-infinite programs”,Mathematics of Operations Research 10 (1985) 207–219.

    Google Scholar 

  21. A. Shapiro, “Asymptotic distribution of test statistics in the analysis of moment structures under inequality constraints”,Biometrika 72 (1985) 133–144.

    Google Scholar 

  22. A. Shapiro, “On differentiability of metric projections in ℝn, 1: Boundary case”, Research Report 6/85, University of South Africa, Pretoria, South Africa.

  23. J.E. Spingarn, “Fixed and variable constraints in sensitivity analysis”,SIAM J. Control and Optimization 18 (1980) 297–310.

    Google Scholar 

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Shapiro, A. Second order sensitivity analysis and asymptotic theory of parametrized nonlinear programs. Mathematical Programming 33, 280–299 (1985). https://doi.org/10.1007/BF01584378

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  • DOI: https://doi.org/10.1007/BF01584378

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