Skip to main content
Log in

Frozen Iterative Methods Using Divided Differences “à la Schmidt–Schwetlick”

  • Published:
Journal of Optimization Theory and Applications Aims and scope Submit manuscript

Abstract

The main goal of this paper is to study the order of convergence and the efficiency of four families of iterative methods using frozen divided differences. The first two families correspond to a generalization of the secant method and the implementation made by Schmidt and Schwetlick. The other two frozen schemes consist of a generalization of Kurchatov method and an improvement of this method applying the technique used by Schmidt and Schwetlick previously. An approximation of the local convergence order is generated by the examples, and it numerically confirms that the order of the methods is well deduced. Moreover, the computational efficiency indexes of the four algorithms are presented and computed in order to compare their efficiency.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Potra, F.A., Pták, V.: Nondiscrete Induction and Iterative Processes. Pitman Publishing, Boston (1984), 250 pp.

    MATH  Google Scholar 

  2. Kurchatov, V.A.: On a method of linear interpolation for the solution of functional equations. Dokl. Akad. Nauk SSSR 198(3), 524–526 (1971). Translation in Sov. Math. Dokl. 12, 835–838 (1971)

    MathSciNet  Google Scholar 

  3. Grau-Sánchez, M., Grau, A., Noguera, M.: Frozen divided difference scheme for solving systems of nonlinear equations. J. Comput. Appl. Math. 235, 1739–1743 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  4. Schmidt, J.W., Schwetlick, H.: Ableitungsfreie Verfahren mit Höherer Konvergenzgeschwindigkeit. Computing 3, 215–226 (1968)

    Article  MATH  MathSciNet  Google Scholar 

  5. Hernández, M.A., Rubio, M.J.: Semilocal convergence of the secant method under mild convergence conditions of differentiability. Comput. Math. Appl. 44, 277–285 (2002)

    Article  MATH  MathSciNet  Google Scholar 

  6. Potra, F.A., Pták, V.: A generalization of Regula Falsi. Numer. Math. 36, 333–346 (1981)

    Article  MATH  Google Scholar 

  7. Shakno, S.M.: On an iterative algorithm with superquadratic convergence for solving nonlinear operator equations. J. Comput. Appl. Math. 231, 222–335 (2009)

    Article  MathSciNet  Google Scholar 

  8. Ezquerro, J.A., Grau-Sánchez, M., Grau, A., Hernández, M.A.: Construction of derivative-free iterative methods from Chebyshev’s method. Anal. Appl. (2012, to appear)

  9. Argyros, I.K., Gutiérrez, J.M.: A unified approach for enlarging the radius of convergence for Newton’s method and applications. Nonlinear Funct. Anal. Appl. 10, 555–563 (2005)

    MATH  MathSciNet  Google Scholar 

  10. Argyros, I.K., Gutiérrez, J.M.: A unifying local and semilocal convergence analysis of Newton-like methods. Adv. Nonlinear Var. Inequal. 10, 1–11 (2007)

    MATH  Google Scholar 

  11. Argyros, I.K.: A Kantorovich-type analysis for a fast iterative method for solving nonlinear equations. J. Math. Anal. Appl. 332, 97–108 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  12. Grau-Sánchez, M., Noguera, M.: A technique to choose the most efficient method between secant method and some variants. Appl. Math. Comput. 218, 6415–6426 (2012)

    Article  MATH  MathSciNet  Google Scholar 

  13. Grau-Sánchez, M., Grau, A., Noguera, M.: On the computational efficiency index and some iterative methods for solving systems of nonlinear equations. J. Comput. Appl. Math. 236, 1259–1266 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  14. Fousse, L., Hanrot, G., Lefèvre, V., elissier P, P., Zimmermann, P.: MPFR: a multiple-precision binary floating-point library with correct rounding. ACM Trans. Math. Softw. 33(2), 13 (2007), 15 pp.

    Article  Google Scholar 

  15. The MPFR library 2.2.0: Timings. http://pari.math.u-bordeaux.fr/benchs/timings-mpfr.html

  16. Grau-Sánchez, M., Noguera, M., Gutiérrez, J.M.: On some computational orders of convergence. Appl. Math. Lett. 23, 472–478 (2010)

    Article  MATH  MathSciNet  Google Scholar 

  17. Ezquerro, J.A., Grau-Sánchez, M., Grau, A., Hernández, M.A., Noguera, M., Romero, N.: On iterative methods with accelerated convergence for solving systems of nonlinear equations. J. Optim. Theory Appl. 151, 163–174 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  18. Weerakoon, S., Fernando, T.G.I.: A variant of Newton’s method with accelerated third-order convergence. Appl. Math. Lett. 13, 87–93 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  19. Brezinski, C.: Accélération de la Convergence en Analyse Numérique. Lecture Notes in Mathematics. Springer, Berlin (1977), 584 pp.

    MATH  Google Scholar 

Download references

Acknowledgements

The research of the three authors has been supported by a grant of the Spanish Ministry of Science and Innovation (Ref. MTM2011-28636-C02-01).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to José M. Gutiérrez.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Grau-Sánchez, M., Noguera, M. & Gutiérrez, J.M. Frozen Iterative Methods Using Divided Differences “à la Schmidt–Schwetlick”. J Optim Theory Appl 160, 931–948 (2014). https://doi.org/10.1007/s10957-012-0216-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10957-012-0216-1

Keywords

Navigation