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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