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Metropolis-Hastings prefetching algorithms

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  • Strid, Ingvar

    (Dept. of Economic Statistics, Stockholm School of Economics)

Abstract

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based on the idea of evaluating the posterior in parallel and ahead of time. In this paper improved Metropolis-Hastings prefetching algorithms are presented and evaluated. It is shown how to use available information to make better predictions of the future states of the chain and increase the efficiency of prefetching considerably. The optimal acceptance rate for the prefetching random walk Metropolis-Hastings algorithm is obtained for a special case and it is shown to decrease in the number of processors employed. The performance of the algorithms is illustrated using a well-known macroeconomic model. Bayesian estimation of DSGE models, linearly or nonlinearly approximated, is identified as a potential area of application for prefetching methods. The generality of the proposed method, however, suggests that it could be applied in many other contexts as well.

Suggested Citation

  • Strid, Ingvar, 2008. "Metropolis-Hastings prefetching algorithms," SSE/EFI Working Paper Series in Economics and Finance 706, Stockholm School of Economics, revised 02 Dec 2009.
  • Handle: RePEc:hhs:hastef:0706
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    References listed on IDEAS

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    10. Ingvar Strid & Karl Walentin, 2009. "Block Kalman Filtering for Large-Scale DSGE Models," Computational Economics, Springer;Society for Computational Economics, vol. 33(3), pages 277-304, April.
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    Cited by:

    1. Edward Herbst & Frank Schorfheide, 2014. "Sequential Monte Carlo Sampling For Dsge Models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(7), pages 1073-1098, November.

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    More about this item

    Keywords

    Prefetching; Metropolis-Hastings; Parallel Computing; DSGE models; Optimal acceptance rate;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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