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A Review of the `BMS' Package for R

  • Shahram Amini

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

  • Christopher F. Parmeter

    (Department of Economics, University of Miami)

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.

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Paper provided by University of Miami, Department of Economics in its series Working Papers with number 2011-8.

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Length: 11 pages
Date of creation: 2011
Date of revision:
Publication status: Forthcoming: Working
Handle: RePEc:mia:wpaper:2011-8
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  1. Yves Croissant & Giovanni Millo, . "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, American Statistical Association, vol. 27(i02).
  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. Martin Feldkircher & Stefan Zeugner, 2009. "Benchmark Priors Revisited: On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging," IMF Working Papers 09/202, International Monetary Fund.
  4. Racine, J & Hyndman, R.J., 2001. "Using R to Teach Econometrics," Monash Econometrics and Business Statistics Working Papers 10/01, Monash University, Department of Econometrics and Business Statistics.
  5. 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.
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