ggmcmc (version 1.5.1.1)

ggs_rocplot: Receiver-Operator Characteristic (ROC) plot for models with binary outcomes

Description

Receiver-Operator Characteristic (ROC) plot for models with binary outcomes

Usage

ggs_rocplot(D, outcome, fully_bayesian = FALSE)

Arguments

D

Data frame whith the simulations. Notice that only the posterior outcomes are needed, and so either the previous call to ggs() should have limited the family of parameters to pass to the predicted outcomes.

outcome

vector (or matrix or array) containing the observed outcome variable. Currently only a vector is supported.

fully_bayesian

logical, false by default. When not fully Bayesian, it uses the median of the predictions for each observation by iteration. When TRUE the function plots as many ROC curves as iterations. It uses a a lot of CPU and needs more memory. Use it with caution.

Value

A ggplot object

Examples

# NOT RUN {
data(binary)
ggs_rocplot(ggs(s.binary, family="mu"), outcome=y.binary)
# }