A Review of the `BMS' Package for R
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.
|Date of creation:||2011|
|Date of revision:|
|Publication status:||Forthcoming: Working|
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- 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).
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- Jeff Racine & Rob Hyndman, 2002.
"Using R to teach econometrics,"
Journal of Applied Econometrics,
John Wiley & Sons, Ltd., vol. 17(2), pages 175-189.
- 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.
- 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.
- 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.
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