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Solving Finite Mixture Models in Parallel

  • Christopher Ferrall

    (Queen's University)

Many 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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File URL: http://128.118.178.162/eps/comp/papers/0303/0303003.pdf
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Paper provided by EconWPA in its series Computational Economics with number 0303003.

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Length: 47 pages
Date of creation: 31 Mar 2003
Date of revision:
Handle: RePEc:wpa:wuwpco:0303003
Note: Type of Document - PDF; prepared on MikTeX; pages: 47; figures: included/
Contact details of provider: Web page: http://128.118.178.162

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  1. Hans M. Amman & David A. Kendrick, . "Computational Economics," Online economics textbooks, SUNY-Oswego, Department of Economics, number comp1, September.
  2. Arcidiacono, Peter & Jones, John B., 2000. "Finite Mixture Distribution, Sequential Likelihood, and the EM Algorithm," Working Papers 00-16, Duke University, Department of Economics.
  3. David Hendry & Neil Shephard & Jurgen Doornik, 2001. "Computationally-intensive Econometrics using a Distributed Matrix-programming Language," Economics Series Working Papers 2001-W22, University of Oxford, Department of Economics.
  4. Jose-Victor Rios-Rull, 1997. "Computation of equilibria in heterogeneous agent models," Staff Report 231, Federal Reserve Bank of Minneapolis.
  5. Victor Aguirregabiria & Pedro Mira, 2002. "Swapping the Nested Fixed Point Algorithm: A Class of Estimators for Discrete Markov Decision Models," Econometrica, Econometric Society, vol. 70(4), pages 1519-1543, July.
  6. Nagurney, Anna, 1996. "Parallel computation," Handbook of Computational Economics, in: H. M. Amman & D. A. Kendrick & J. Rust (ed.), Handbook of Computational Economics, edition 1, volume 1, chapter 7, pages 335-404 Elsevier.
  7. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
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