quantFit {fairadapt} | R Documentation |
Quality of quantile fit statistics.
Description
Quality of quantile fit statistics.
Usage
quantFit(x, ...)
Arguments
x |
Object of class |
... |
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)
[Package fairadapt version 0.2.7 Index]