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Embarrassingly Easy Embarrassingly Parallel Processing in R: Implementation and Reproducibility

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  • Michael S. Delgado

    (Department of Agricultural Economics, Purdue University)

  • Christopher F. Parmeter

    (Department of Economics, University of Miami)

Abstract

No abstract is available for this item.

Suggested Citation

  • Michael S. Delgado & Christopher F. Parmeter, 2013. "Embarrassingly Easy Embarrassingly Parallel Processing in R: Implementation and Reproducibility," Working Papers 2013-06, University of Miami, Department of Economics.
    • Handle: RePEc:mia:wpaper:2013-06
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    File URL: https://www.herbert.miami.edu/_assets/files/repec/WP2013-06.pdf
    File Function: First version, 2013
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    References listed on IDEAS

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    1. Anson T. Y. Ho & Kim P. Huynh & David T. Jacho‐Chávez, 2011. "npRmpi: A package for parallel distributed kernel estimation in R," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(2), pages 344-349, March.
    2. Michael Creel, 2007. "I ran four million probits last night: HPC clustering with ParallelKnoppix," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(1), pages 215-223.
    3. Swann, Christopher A, 2002. "Maximum Likelihood Estimation Using Parallel Computing: An Introduction to MPI," Computational Economics, Springer;Society for Computational Economics, vol. 19(2), pages 145-178, April.
    4. Christopher A. Swann, 2001. "Software for parallel computing: the LAM implementation of MPI," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(2), pages 185-194.
    5. Roger Koenker & Achim Zeileis, 2009. "On reproducible econometric research," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(5), pages 833-847.
    6. Michael Creel, 2005. "User-Friendly Parallel Computations with Econometric Examples," Computational Economics, Springer;Society for Computational Economics, vol. 26(2), pages 107-128, October.
    7. Evan Meredith & Jeffrey S. Racine, 2009. "Towards reproducible econometric research: the Sweave framework," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(2), pages 366-374, March.
    8. L’Ecuyer, Pierre & Simard, Richard, 2001. "On the performance of birthday spacings tests with certain families of random number generators," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 55(1), pages 131-137.
    9. Manuel Eugster & Jochen Knaus & Christine Porzelius & Markus Schmidberger & Esmeralda Vicedo, 2011. "Hands-on tutorial for parallel computing with R," Computational Statistics, Springer, vol. 26(2), pages 219-239, June.
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    Cited by:

    1. Delgado, Michael S. & Parmeter, Christopher F., 2014. "A simple estimator for partial linear regression with endogenous nonparametric variables," Economics Letters, Elsevier, vol. 124(1), pages 100-103.
    2. Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
    3. Tsionas, Mike G., 2021. "Optimal combinations of stochastic frontier and data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 294(2), pages 790-800.

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    Keywords

    Parallel processing; reproducibility; computational efficiency; bootstrap; nonlinear optimization; Monte Carlo;
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