In this paper we present and analyze a set of predictor-corrector iterative methods with increasing order of convergence, for solving systems of nonlinear equations. Our aim is to achieve high order of convergence with few Jacobian and/or functional evaluations. On the other hand, by applying the pseudocomposition technique on each proposed scheme we get to increase their order of convergence, obtaining new high-order and efficient methods. We use the classical efficiency index in order to compare the obtained schemes and make some numerical test. © 2013 Springer-Verlag.
CITATION STYLE
Cordero, A., Torregrosa, J. R., & Vassileva, M. P. (2013). New family of iterative methods with high order of convergence for solving nonlinear systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8236 LNCS, pp. 222–230). https://doi.org/10.1007/978-3-642-41515-9_23
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