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

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

print_fit(..., ic = "looic", ncore = 2, round_to = 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

round_to

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

Value

model_table 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
print_fit(output1, output2)

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

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