Print model-fits (mean LOOIC or WAIC values in addition to Akaike weights) of hBayesDM Models

printFit(..., ic = "looic", ncore = 2, roundTo = 3)



Model objects output by hBayesDM functions (e.g. output1, output2, etc.)


Which model comparison information criterion to use? 'looic', 'waic', or 'both


Number of corse to use when computing LOOIC


Number of digits to the right of the decimal point in the output


modelTable A table with relevant model comparison data. LOOIC and WAIC weights are computed as Akaike weights.


if (FALSE) {
# Run two models and store results in "output1" and "output2"
output1 <- dd_hyperbolic("example", 2000, 1000, 3, 3)

output2 <- dd_exp("example", 2000, 1000, 3, 3)

# Show the LOOIC model fit estimates
printFit(output1, output2)

# To show the WAIC model fit estimates
printFit(output1, output2, ic = "waic")

# To show both LOOIC and WAIC
printFit(output1, output2, ic = "both")