summary.bma {BMS} | R Documentation |
Returns a vector with summary statistics for a 'bma' object
## S3 method for class 'bma' summary(object,...) ## or info.bma(object,...)
object |
a list/object of class 'bma' that typically results from the function |
... |
further arguments passed to or from other methods |
info.bma
is equivalent to summary.bma
, its argument bmao
conforms to the argument object
A character vector summarizing the results of a call to bms
Mean no. of Regressors |
the posterior mean of model size |
Draws |
the number of iterations (ex burn-ins) |
Burnins |
the number of burn-in iterations |
Time |
the time spent on iterating through the model space |
No. of models visited |
the number of times a model was accepted (including burn-ins) |
Modelspace 2^K |
the total model space 2^K |
Percentage visited |
|
Percentage Topmodels |
number of times the best models were drawn in percent of |
Corr. PMP |
the correlation between the MCMC frequencies of the best models (the number of times they were drawn) and their marginal likelihoods. |
No. Obs. |
Number of observations |
Model Prior |
a character conforming to the argument |
g-prior |
a character corresponding to argument |
Shrinkage-Stats |
Posterior expected value und standard deviation (if applicable) of the shrinkage factor. Only included if argument |
All of the above statistics can also be directly extracted from the bma object (bmao
). Therefore summary.bma
only returns a character vector.
Martin Feldkircher and Stefan Zeugner
bms
and c.bma
for functions creating bma objects, print.bma
makes use of summary.bma
.
Check http://bms.zeugner.eu for additional help.
data(datafls) m_fixed=bms(datafls,burn=1000,iter=3000,user.int=FALSE, ) summary(m_fixed) m_ebl=bms(datafls,burn=1000,iter=3000,user.int=FALSE, g="EBL",g.stats=TRUE) info.bma(m_ebl)