# Computing Bayes Factor using “Bayesfactor” package

For the purpose of model selection, I am using the Bayes' factor to compare different combinations of predictors in a linear regression model.

I have used the function regressionBF() from the library(BayesFactor), and I got the following results:

# > regressionBF(return ~ FSCR + VAL, data = dataf)

# Bayes factor analysis
# --------------
#[1] FSCR       : 65.17482  ±0%
#[2] VAL        : 0.1979875 ±0.02%
#[3] FSCR + VAL : 23.58704  ±0%

#Against denominator:
#  Intercept only


I am not sure how to interpret these results. What do the percentage numbers next to the Bayes' factors mean? Also, 65 and 23 seem pretty high for a Bayes' factor. How can I interpret that?

Any help would be appreciated. Thanks!

• In the rest of the package, the BF is followed by the proportional error estimate on the Bayes factor, that's probably the 2nd number. A BF of 65 against the null doesn't seem implausible. – jona Sep 12 '13 at 14:18
• Thanks for your comment. Would a BF = 65 be a "strong/decisive" evidence for the alternative? Also, I am not sure what you mean by proportional error estimate... – Mayou Sep 12 '13 at 14:19