Investigating Convergence Patterns for Numerical Methods Using Data Analysis

• Autores: Sheldon P. Gordon
• Localización: Primus: problems, resources, and issues in mathematics undergraduate studies, ISSN 1051-1970, Vol. 23, Nº. 8, 2013, págs. 703-717
• Idioma: inglés
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• Resumen

  • The article investigates the patterns that arise in the convergence of numerical methods, particularly those in the errors involved in successive iterations, using data analysis and curve fitting methods. In particular, the results obtained are used to convey a deeper level of understanding of the concepts of linear, quadratic, and cubic convergence. In addition, the issue estimating the number of additional correct digits on each successive iteration is also considered.