Solving Finite Mixture Models in Parallel
AbstractMany economic models are completed by finding a parameter vector that optimizes a function f, a task that only be accomplished by iterating from a starting vector. Use of a generic iterative optimizer to carry out this task can waste enormous amounts of computation when applied to a class of problems defined here as finite mixture models. The finite mixture class is large and important in economics and eliminating wasted computations requires only limited changes to standard code. Further, the approach described here greatly increases gains from parallel execution and opens possibilities for re-writing objective functions to make further efficiency gains.
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Bibliographic InfoPaper provided by EconWPA in its series Computational Economics with number 0303003.
Length: 47 pages
Date of creation: 31 Mar 2003
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Numerical Optimization; Heterogeneous Agent Models;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-04-09 (All new papers)
- NEP-CMP-2003-04-09 (Computational Economics)
- NEP-ECM-2003-04-12 (Econometrics)
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