Inexact Newton methods for model simulation

  title={Inexact Newton methods for model simulation},
  author={Stefania Bellavia and Silvia Magheri and Claudia Miani},
  journal={International Journal of Computer Mathematics},
  pages={2969 - 2987}
Robust and efficient solution techniques for solving macroeconometric models are increasingly becoming a key factor in developing models employed by policy-making institutions for policy simulations and forecasting. Traditionally, when solved in the presence of forward-looking variables, these models are nonlinear, large-scale and sparse and give rise to large and highly structured nonlinear systems. This paper proposes a Newton-GMRES method obtained tuning up the basic algorithm by properly… 


Krylov methods for solving models with forward-looking variables
An alternative methodology for solving nonlinear forward-looking models
Solution and Maximum Likelihood Estimation of Dynamic Nonlinear Rationalexpectations Models
A solution method and an estimation method for nonlinear rational expectations models are presented in this paper. The solution method can be used in forecasting and policy applications and can
Globalization Techniques for Newton-Krylov Methods and Applications to the Fully Coupled Solution of the Navier-Stokes Equations
This paper reviews several representative globalizations of Newton-Krylov methods, discusses their properties, and reports on a numerical study aimed at evaluating their relative merits on large-scale two- and three-dimensional problems involving the steady-state Navier-Stokes equations.
Beyond Newton: Robust Methods For Solving Large Nonlinear Models In Troll
Enhanced to Newton's Method used in the TROLL modeling system is described and enhancements with a variety of contemporary models are illustrated.
NITSOL: A Newton Iterative Solver for Nonlinear Systems
A well-developed Newton iterative (truncated Newton) algorithm for solving large-scale nonlinear systems that is implemented in a Fortran solver called NITSOL that is robust yet easy to use and provides a number of useful options and features.
Inexact Newton Dogleg Methods
This paper outlines a very general dogleg method suitable for the general inexact Newton context and provides a global convergence analysis for it, and discusses certain issues that may arise with the standard dogleg implementational strategy and proposes modified strategies that address them.
A Globally Convergent Newton-GMRES Subspace Method for Systems of Nonlinear Equations
This work introduces a new hybrid Newton-GMRES method where a global strategy restricted to a low-dimensional subspace generated by GMRES is performed and enhances the classical backtracking inexact method.
Convergence Theory of Nonlinear Newton-Krylov Algorithms
Some convergence theory for nonlinear Krylov subspace methods is presented, to analyze these methods when they are combined with global strategies such as linesearch techniques and model trust region algorithms.