View source: R/hypothesis_test.r
PerfCurveTest | R Documentation |
PerfCurveTest
takes score vectors for two scoring algorithms and an activity vector.
A performance curve is created for the two scoring algorithms and hypothesis tests are performed
at the selected testing fractions.
PerfCurveTest(
S1,
S2,
X,
r,
metric = "rec",
method = "EmProc",
type = "pointwise",
plus = T,
pool = F,
alpha = 0.05,
h = NULL,
seed = 111,
mc.rep = 1e+05
)
S1 |
a vector of scores for scoring algorithm 1. |
S2 |
a vector of scores for scoring algorithm 2. |
X |
a vector of activities. |
r |
a vector of testing fractions. |
metric |
the performance curve to use. Options are recall ("rec") and precision ("prec"). |
method |
the method to use. Recall options are c("EmProc", "binomial", "JZ ind", "mcnemar", "binomial ind"). Precision options are c("EmProc", "binomial", "JZ ind", "stouffer", "binomial ind"). |
type |
specifies whether a point-wise confidence interval ("pointwise") or a confidence band ("band") should be constructed. |
plus |
should plus correction be applied to the confidence intervals? |
pool |
use pooling for hypothesis tests? Only relevant to "EmProc". |
alpha |
the significance level. |
h |
the bandwidth for the local regression estimator of Lambda. If NULL, uses the default plugin estimator. |
seed |
the random seed. |
mc.rep |
the number of Monte Carlo replicates to use for the sup-t method. |
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