printFit: 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

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

## 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
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")

## End(Not run)

hBayesDM documentation built on Sept. 23, 2022, 9:06 a.m.