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As you say in your paper that the inference for pi is quite accurate (compare to full MCMC), I think it would be of interest to show it in the output of print.summary.varbvs. For that, if I'm not wrong, I think one could add the following commands, for instance just before the line "Selected variables by probability cutoff":
I tend to think that some users prefer pi and others logodds, hence both could be reported. To avoid confusion, you could simply add a sentence in the manual saying that one can be obtain from the other.
@timflutre I'm going to leave this open for now, but I have added a sentence about converting between the prior log-odds and the prior inclusion probability (see commit 022e0da). Part of the issue here is that I don't have a consistent notation for the prior inclusion probability (pi is awkward).
As you say in your paper that the inference for pi is quite accurate (compare to full MCMC), I think it would be of interest to show it in the output of
print.summary.varbvs
. For that, if I'm not wrong, I think one could add the following commands, for instance just before the line "Selected variables by probability cutoff":and then:
What do you think?
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