Bayesian Model Averaging and Jointness Measures for gretl
This paper presents a software package that implements Bayesian model averaging for Gnu Regression, Econometrics and Time-series Library - gretl. The Bayesian Model Averaging (BMA) is a model-building strategy that takes account of model uncertainty into conclusions about estimated parameters. It is an efficient tool for discovering the most probable models and obtaining estimates of their posterior characteristics. In recent years we have observed an increasing number of software package devoted to BMA for different statistical and econometric software. In this paper, we propose BMA package for gretl, which is more and more popular free, open-source software for econometric analysis with easy-to-use GUI. We introduce BMA package for the linear regression models with jointness measures proposed by Ley and Steel (2007) and Doppelhofer and Weeks (2009).
|Date of creation:||10 Feb 2013|
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- Enrique Moral-Benito, 2011.
"Model averaging in economics,"
Banco de Espa�a Working Papers
1123, Banco de Espa�a.
- Ley, Eduardo & Steel, Mark F. J., 2006.
"Jointness in Bayesian variable selection with applications to growth regression,"
Policy Research Working Paper Series
4063, The World Bank.
- Ley, Eduardo & Steel, Mark F.J., 2007. "Jointness in Bayesian variable selection with applications to growth regression," Journal of Macroeconomics, Elsevier, vol. 29(3), pages 476-493, September.
- Shahram Amini & Christopher F. Parmeter, 2011. "Bayesian Model Averaging in R," Working Papers 2011-9, University of Miami, Department of Economics.
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