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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- 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.
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- 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.
- 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.
- 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.
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