The Nelder-Mead simplex method is an optimization routine that works well with irregular objective functions. For a function of <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$n$$</EquationSource> </InlineEquation> parameters, it compares the objective function at the <InlineEquation ID="IEq2"> <EquationSource Format="TEX">$$n+1$$</EquationSource> </InlineEquation> vertices of a simplex and updates the worst vertex through simplex search steps. However, a...</equationsource></inlineequation></equationsource></inlineequation>

This paper investigates parallel solution methods to simulate large-scale macroeconometric models with forward-looking variables. The method chosen is the Newton-Krylov algorithm, and we concentrate on a parallel solution to the sparse linear system arising in the Newton algorithm. We...

We implement a dynamic programming algorithm on a computational grid consisting of loosely coupled processors, possibly including clusters and individual workstations. The grid changes dynamically during the computation, as processors enter and leave the pool of workstations. The algorithm is...

This paper shows how a high-level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of...