# NOT RUN {
data(vur.test)
fairness.profile.plot(response = vur.test$y, predictors = vur.test$X,
sensitive = vur.test$S, type = "coefficients", model = "nclm", legend = TRUE)
fairness.profile.plot(response = vur.test$y, predictors = vur.test$X,
sensitive = vur.test$S, type = "constraints", model = "nclm", legend = TRUE)
fairness.profile.plot(response = vur.test$y, predictors = vur.test$X,
sensitive = vur.test$S, type = "rmse", model = "nclm", legend = TRUE)
# profile plots fitting models in parallel.
# }
# NOT RUN {
library(parallel)
cl = makeCluster(2)
fairness.profile.plot(response = vur.test$y, predictors = vur.test$X,
sensitive = vur.test$S, model = "nclm", cluster = cl)
stopCluster(cl)
# }
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