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) { # \dontrun{
# 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")
} # }