| info.bma {BMS} | R Documentation |
Returns a vector with summary statistics for a 'bma' object
info.bma(bmao) ## S3 method for class 'bma' summary(object, ...)
bmao |
same as |
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 |
the total model space 2^K |
list(list("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.
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)