fart defines a decision's false alarm rate
(or the rate of false positives): The conditional probability
of the decision being positive if the condition is FALSE.
An object of class
numeric of length 1.
Understanding or obtaining the false alarm rate
fart is the conditional probability
for an incorrect positive decision given that
the condition is
fart = p(decision = positive | condition = FALSE)
or the probability of a false alarm.
fart further classifies
the subset of
by decision (
fart = fa/cond_false).
false positive rate (
rate of type-I errors (
statistical significance level,
fart is the complement of the
fart = 1 - spec
fart is the opposite conditional probability
-- but not the complement --
of the false discovery rate
or false detection rate
FDR = p(condition = FALSE | decision = positive)
fart = fa/cond_false = fa/(fa + cr)
fart is a feature of a decision process
or diagnostic procedure and a measure of
incorrect decisions (false positives).
However, due to being a conditional probability,
the value of
fart is not intrinsic to
the decision process, but also depends on the
condition's prevalence value
Consult Wikipedia for additional information.
fart as the complement of
prob contains current probability information;
comp_prob computes current probability information;
num contains basic numeric parameters;
init_num initializes basic numeric parameters;
comp_freq computes current frequency information;
is_prob verifies probabilities.
fart <- .25 # sets a false alarm rate of 25% fart <- 25/100 # (decision = positive) for 25 out of 100 people with (condition = FALSE) is_prob(fart) # TRUE#>  TRUE