bpcs (version 1.0.0)

get_waic: Tiny wrapper for the WAIC method from the loo package.

Description

This is used to evaluate the fit of the model using the Watanabe-Akaike Information criteria

Usage

get_waic(bpc_object)

Arguments

bpc_object

a bpc object

Value

a loo object

References

Gelman, Andrew, Jessica Hwang, and Aki Vehtari. Understanding predictive information criteria for Bayesian models. Statistics and computing 24.6 (2014): 997-1016.

Examples

# NOT RUN {
m<-bpc(data = tennis_agresti,
player0 = 'player0',
player1 = 'player1',
result_column = 'y',
model_type = 'bt',
solve_ties = 'none')
waic<-get_waic(m)
print(waic)
# }