| gprior-class {BMS} | R Documentation |
Class "gprior"
Description
An object pertaining to a coefficient prior
Objects from the Class
A gprior object holds descriptions
and subfunctions pertaining to coefficient priors. Functions such as
bms or zlm rely on this class to 'convert' the
output of OLS results into posterior expressions for a Bayesian Linear
Model. Post-processing functions such as density.bma also
resort to gprior objects.
There are currently three coefficient prior
structures built into the BMS package, generated by the following functions
(cf. Feldkircher and Zeugner, 2009) :
gprior.constg.init: creates
a Zellner's g-prior object with constant g.
gprior.eblocal.init: creates an Empricial Bayes Zellner's g-prior.
gprior.hyperg.init: creates a hyper g-prior with a Beta-prior on the
shrinkage parameter.
The following describes the necessary slots
Author(s)
Martin Feldkircher and Stefan Zeugner
References
Feldkircher, M. and S. Zeugner (2009): Benchmark Priors Revisited: On Adaptive Shrinkage and the Supermodel Effect in Bayesian Model Averaging, IMF Working Paper 09/202.
See Also
bms and zlm for creating bma or
zlm objects.
Check the appendix of vignette(BMS) for a
more detailed description of built-in priors.
Check
http://bms.zeugner.eu/custompriors.php for examples.
Examples
data(datafls)
mm1=bms(datafls[,1:10], g="EBL")
gg=mm1$gprior.info # is the g-prior object, augmented with some posterior statistics
mm2=bms(datafls[,1:10], g=gg) #produces the same result
mm3=bms(datafls[,1:10], g=BMS:::.gprior.eblocal.init)
#this passes BMS's internal Empirical Bayes g-prior object as the coefficient prior
# - any other obejct might be used as well