FDR defines a decision's false detection (or false discovery)
FDR): The conditional probability of the condition
FALSE provided that the decision is positive.
An object of class
numeric of length 1.
Understanding or obtaining the false detection fate
or false discovery rate (
FDR is the conditional probability
for the condition being
given a positive decision:
FDR = p(condition = FALSE | decision = positive)
FDR further classifies
the subset of
by condition (
FDR = fa/dec_pos = fa/(hi + fa)).
Alternative names: false discovery rate
FDR is the complement of the
positive predictive value
FDR = 1 - PPV
FDR is the opposite conditional probability
– but not the complement –
of the false alarm rate
fart = p(decision = positive | condition = FALSE)
In terms of frequencies,
FDR is the ratio of
fa divided by
hi + fa):
FDR = fa/dec_pos = fa/(hi + fa)
FDR is a feature of a decision process
or diagnostic procedure and
a measure of incorrect decisions (positive decisions
that are actually
However, due to being a conditional probability,
the value of
FDR is not intrinsic to
the decision process, but also depends on the
condition's prevalence value
Consult Wikipedia for additional information.
prob contains current probability information;
comp_prob computes current probability information;
num contains basic numeric parameters;
init_num initializes basic numeric parameters;
freq contains current frequency information;
comp_freq computes current frequency information;
is_prob verifies probabilities.
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