PerfCurveBands takes a pair of score and activity vectors as input.
A performance curve and confidence band is created for the selected testing fractions.
PerfCurveBands(
S,
X,
r,
metric = "rec",
type = "band",
method = "sup-t",
plus = T,
conf.level = 0.95,
boot.rep = 100,
mc.rep = 1e+05,
myseed = 111,
h = NULL
)a vector of scores.
a vector of activities.
a vector of testing fractions.
the performance curve to use. Options are recall ("rec") and precision ("prec").
specifies whether a point-wise confidence interval ("pointwise") or a confidence band ("band") should be constructed.
the method to use. Point-wise confidence interval options are "binomial", "JZ", "bootstrap". Confidence band options are "sup-t", "theta-proj".
should plus correction be used or not?
the confidence level for the bands.
the number of replicates to use for the bootstrap method.
the number of Monte Carlo replicates to use for the sup-t method.
the random seed.
the bandwidth for the local regression estimator of Lambda. If NULL, uses the default plugin estimator.