Quality of quantile fit statistics.

quantFit(x, ...)

Arguments

x: Object of class fairadapt, a result of an adaptation procedure.
...: Ignored in this case.

Value

A numeric vector, containing the average empirical loss for the 25%, 50% and 75% quantile loss functions, for each variable.

Examples

n_samp <- 200
uni_dim <- c(       "gender", "edu", "test", "score")
uni_adj <- matrix(c(       0,     1,      1,       0,
                           0,     0,      1,       1,
                           0,     0,      0,       1,
                           0,     0,      0,       0),
                  ncol = length(uni_dim),
                  dimnames = rep(list(uni_dim), 2),
                  byrow = TRUE)

uni_ada <- fairadapt(score ~ .,
  train.data = head(uni_admission, n = n_samp),
  test.data = tail(uni_admission, n = n_samp),
  adj.mat = uni_adj,
  prot.attr = "gender",
  eval.qfit = 3L
)

quantFit(uni_ada)
#>       edu      test     score 
#> 0.3463112 0.2601742 0.3283719