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A Review of the `BMS' Package for R

Author

Listed:
  • Shahram Amini

    (Department of Economics, Virginia Polytechnic Institute and State University)

  • Christopher F. Parmeter

    (Department of Economics, University of Miami)

Abstract

This paper describes the relative merits and attractiveness of the newest Bayesian model averaging package, BMS, available in the statistical software R to implement a Bayesian model averaging exercise. This package provides the user with a wide range of customizable priors for conducting a BMA analysis, provides ample graphs to visualize the results and offers several alternative model search mechanisms.

Suggested Citation

  • Shahram Amini & Christopher F. Parmeter, 2011. "A Review of the `BMS' Package for R," Working Papers 2011-8, University of Miami, Department of Economics.
    • Handle: RePEc:mia:wpaper:2011-8
    as

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    File URL: https://www.herbert.miami.edu/_assets/files/repec/wp2011-8.pdf
    File Function: First version, 2011
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    References listed on IDEAS

    as
    1. Jeff Racine & Rob Hyndman, 2002. "Using R to teach econometrics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(2), pages 175-189.
    2. Harrison, David Jr. & Rubinfeld, Daniel L., 1978. "Hedonic housing prices and the demand for clean air," Journal of Environmental Economics and Management, Elsevier, vol. 5(1), pages 81-102, March.
    3. Liang, Feng & Paulo, Rui & Molina, German & Clyde, Merlise A. & Berger, Jim O., 2008. "Mixtures of g Priors for Bayesian Variable Selection," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 410-423, March.
    4. Ley, Eduardo & Steel, Mark F. J., 2007. "On the effect of prior assumptions in Bayesian model averaging with applications to growth regression," Policy Research Working Paper Series 4238, The World Bank.
    5. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    Full references (including those not matched with items on IDEAS)

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    JEL classification:

    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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