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

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

Arguments

...

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

ic

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

ncore

Number of corse to use when computing LOOIC

roundTo

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

Value

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

Examples

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") }