print_fit: Print model-fits (mean LOOIC or WAIC values in addition to...

In hBayesDM: Hierarchical Bayesian Modeling of Decision-Making Tasks

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

Description

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

Usage

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

## Not run: 
# 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")

## End(Not run)

hBayesDM documentation built on Sept. 10, 2026, 1:12 a.m.