  Minimum Bayes factors are commonly used to transform two-sided p-values to
lower bounds on the posterior probability of the null hypothesis, as in
Pericchi et al. (2017). In this article, we show posterior probabilities of
hypothesis by transforming the commonly used -eplog(p), proposed by Vovk (1993)
and Sellke et al. (2001). This is achieved after adjusting this minimum Bayes
factor with the information to approximate it to an exact Bayes factor, not
only when p is a p-value but also when p is a pseudo p-value in the sense of
Casella and Berger (2001). Additionally, we show the fit to a refined version
to linear models.
