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Estimating upper bounds on the limit points of majorizing sequences for Newton’s method

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Abstract

We present new sufficient conditions for the semilocal convergence of Newton’s method to a locally unique solution of an equation in a Banach space setting. Upper bounds on the limit points of majorizing sequences are also given. Numerical examples are provided, where our new results compare favorably to earlier ones such as Argyros (J Math Anal Appl 298:374–397, 2004), Argyros and Hilout (J Comput Appl Math 234:2993-3006, 2010, 2011), Ortega and Rheinboldt (1970) and Potra and Pták (1984).

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References

  1. Amat, S., Busquier, S., Negra, M.: Adaptive approximation of nonlinear operators. Numer. Funct. Anal. Optim. 25, 397–405 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  2. Argyros, I.K.: A unifying local-semilocal convergence analysis and applications for two-point Newton-like methods in Banach space. J. Math. Anal. Appl. 298, 374–397 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  3. Argyros, I.K.: On the Newton-Kantorovich hypothesis for solving equations. J. Comput. Appl. Math. 169, 315–332 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  4. Argyros, I.K.: Concerning the “terra incognita” between convergence regions of two Newton methods. Nonlinear Anal. 62, 179–194 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  5. Argyros, I.K.: Approximating solutions of equations using Newton’s method with a modified Newton’s method iterate as a starting point. Rev. Anal. Numér. Théor. Approx. 36(2), 123–138 (2007)

    MathSciNet  MATH  Google Scholar 

  6. Argyros, I.K.: Computational theory of iterative methods. In: Chui, C.K., Wuytack, L. (eds.): Series: Studies in Computational Mathematics, vol. 15. Elsevier Publ. Co., New York (2007)

    Google Scholar 

  7. Argyros, I.K.: On a class of Newton-like methods for solving nonlinear equations. J. Comput. Appl. Math. 228, 115–122 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  8. Argyros, I.K.: A semilocal convergence analysis for directional Newton methods. Math. Comput. 80, 327–343 (2011)

    Article  MATH  Google Scholar 

  9. Argyros, I.K., Hilout, S.: Efficient Methods for Solving Equations and Variational Inequalities. Polimetrica Publisher, Milano, Italy (2009)

    Google Scholar 

  10. Argyros, I.K., Hilout, S.: Enclosing roots of polynomial equations and their applications to iterative processes. Surveys Math. Appl. 4, 119–132 (2009)

    MathSciNet  MATH  Google Scholar 

  11. Argyros, I.K., Hilout, S.: Extending the Newton-Kantorovich hypothesis for solving equations. J. Comput. Appl. Math. 234, 2993–3006 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  12. Argyros, I.K., Hilout, S.: Improved local convergence of Newton’s method under weak majorant condition. J. Comput. Appl. Math. 236, 1892–1902 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  13. Argyros, I.K., Hilout, S.: Majorizing sequences for iterative methods. J. Comput. Appl. Math. 236, 1947–1960 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  14. Argyros, I.K., Hilout, S.: Weaker conditions for the convergence of Newton’s method. J. Complexity. (2012). doi:10.1016/j.jco.2011.12.003

    Google Scholar 

  15. Argyros, I.K., Hilout, S., Tabatabai, M.A.: Mathematical Modelling with Applications in Biosciences and Engineering. Nova Publishers, New York (2011)

    Google Scholar 

  16. Bi, W., Wu, Q., Ren, H.: Convergence ball and error analysis of Ostrowski-Traub’s method. Appl. Math. J. Chinese Univ. Ser. B. 25, 374–378 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  17. Cătinaş, E.: The inexact, inexact perturbed, and quasi-Newton methods are equivalent models. Math. Comp. 74(249), 291–301 (2005)

    MathSciNet  MATH  Google Scholar 

  18. Chen, X., Yamamoto, T.: Convergence domains of certain iterative methods for solving nonlinear equations. Numer. Funct. Anal. Optim. 10, 37–48 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  19. Deuflhard, P.: Newton methods for nonlinear problems. Affine invariance and adaptive algorithms. In: Springer Series in Computational Mathematics, vol. 35, Springer, Berlin (2004)

    Google Scholar 

  20. Ezquerro, J.A., Gutiérrez, J.M., Hernández, M.A., Romero, N., Rubio, M.J.: The Newton method: from Newton to Kantorovich (Spanish). Gac. R. Soc. Mat. Esp. 13(1), 53–76 (2010)

    MathSciNet  MATH  Google Scholar 

  21. Ezquerro, J.A., Hernández, M.A.: On the R-order of convergence of Newton’s method under mild differentiability conditions. J. Comput. Appl. Math. 197(1), 53–61 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  22. Ezquerro, J.A., Hernández, M.A.: An improvement of the region of accessibility of Chebyshev’s method from Newton’s method. Math. Comp. 78(267), 1613–1627 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  23. Ezquerro, J.A., Hernández, M.A., Romero, N.: Newton-type methods of high order and domains of semilocal and global convergence. Appl. Math. Comput. 214(1), 142–154 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  24. Gragg, W.B., Tapia, R.A.: Optimal error bounds for the Newton-Kantorovich theorem. SIAM J. Numer. Anal. 11, 10–13 (1974)

    Article  MathSciNet  MATH  Google Scholar 

  25. Hernández, M.A.: A modification of the classical Kantorovich conditions for Newton’s method. J. Comput. Appl. Math. 137, 201–205 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  26. Kantorovich, L.V., Akilov, G.P.: Functional Analysis. Pergamon Press, Oxford (1982)

    MATH  Google Scholar 

  27. Ortega, L.M., Rheinboldt, W.C.: Iterative Solution of Nonlinear Equations in Several Variables. Academic Press, New York (1970)

    MATH  Google Scholar 

  28. Ostrowski, A.M.: Sur la convergence et l’estimation des erreurs dans quelques procédés de résolution des équations numériques (French). Memorial volume dedicated to D. A. Grave [Sbornik posvjaščenii pamjati D. A. Grave], pp. 213–234. Moscow (1940)

  29. Ostrowski, A.M.: La méthode de Newton dans les espaces de Banach. C. R. Acad. Sci. Paris Sér. A–B. 272, 1251–1253 (1971)

    MathSciNet  MATH  Google Scholar 

  30. Ostrowski, A.M.: Solution of Equations in Euclidean and Banach Spaces. Academic press, New York (1973)

    MATH  Google Scholar 

  31. Păvăloiu, I.: Introduction in the theory of approximation of equations solutions. Dacia Ed., Cluj-Napoca. (1976)

    Google Scholar 

  32. Potra, F.A.: The rate of convergence of a modified Newton’s process. With a loose Russian summary. Appl. Math. 26(1), 13–17 (1981)

    MathSciNet  MATH  Google Scholar 

  33. Potra, F.A.: An error analysis for the secant method. Numer. Math. 38, 427–445 (1981/1982)

    Article  MathSciNet  MATH  Google Scholar 

  34. Potra, F.A.: On the convergence of a class of Newton-like methods. In: Iterative Solution of Nonlinear Systems of Equations (Oberwolfach, 1982), pp. 125–137. Lecture Notes in Math., vol. 953. Springer, Berlin-New York (1982)

    Chapter  Google Scholar 

  35. Potra, F.A.: Sharp error bounds for a class of Newton-like methods. Libertas Mathematica 5, 71–84 (1985)

    MathSciNet  MATH  Google Scholar 

  36. Potra, F.A., Pták, V.: Sharp error bounds for Newton’s process. Numer. Math. 34(1), 63–72 (1980)

    Article  MathSciNet  MATH  Google Scholar 

  37. Potra, F.A., Pták, V.: Nondiscrete induction and iterative processes. Research Notes in Mathematics, vol. 103. Pitman (Advanced Publishing Program), Boston, MA (1984)

    Google Scholar 

  38. Proinov, P.D.: General local convergence theory for a class of iterative processes and its applications to Newton’s method. J. Complex. 25, 38–62 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  39. Proinov, P.D.: New general convergence theory for iterative processes and its applications to Newton-Kantorovich type theorems. J. Complex. 26, 3–42 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  40. Rall, L.B.: Computational Solution of Nonlinear Operator Equations. Wiley, New–York (1969)

    Google Scholar 

  41. Rheinboldt, W.C.: A unified convergence theory for a class of iterative processes. SIAM J. Numer. Anal. 5, 42–63 (1968)

    Article  MathSciNet  MATH  Google Scholar 

  42. Rheinboldt, W.C.: An adaptive continuation process for solving systems of nonlinear equations. Pol. Acad. Sci. 3, 129–142 (1977)

    MathSciNet  Google Scholar 

  43. Tapia, R.A.: Classroom notes: the Kantorovich theorem for Newton’s method. Am. Math. Mon. 78, 389–392 (1971)

    Article  MathSciNet  MATH  Google Scholar 

  44. Traub, J.F., Woźniakowsi, H.: Convergence and complexity of Newton iteration for operator equations. J. Assoc. Comput. Mach. 26, 250–258 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  45. Wu, Q., Ren, H.: A note on some new iterative methods with third-order convergence. Appl. Math. Comput. 188, 1790–1793 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  46. Yamamoto, T.: A convergence theorem for Newton-like methods in Banach spaces. Numer. Math. 51, 545–557 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  47. Zabrejko, P.P., Nguen, D.F.: The majorant method in the theory of Newton-Kantorovich approximations and the Pták error estimates. Numer. Funct. Anal. Optim. 9, 671–684 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  48. Zinc̆enko, A.I.: Some approximate methods of solving equations with non-differentiable operators. (Ukrainian). Dopov Akad. Nauk Ukr. RSR 115, 156–161 (1963)

    MathSciNet  Google Scholar 

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Correspondence to Ioannis K. Argyros.

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Argyros, I.K., Hilout, S. Estimating upper bounds on the limit points of majorizing sequences for Newton’s method. Numer Algor 62, 115–132 (2013). https://doi.org/10.1007/s11075-012-9570-1

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