mi is the frequency of misses
or false negatives (
in a population of
An object of class
numeric of length 1.
mi is the frequency of individuals for which
Condition = TRUE and
Decision = FALSE (negative).
mi is a measure of incorrect classifications
(type-II errors), not an individual case.
mi depends on the miss rate
(aka. false negative rate, FNR)
and is conditional on the prevalence
to other frequencies:
In a population of size
the following relationships hold:
N = cond_true + cond_false (by condition)
N = dec_pos + dec_neg (by decision)
N = dec_cor + dec_err (by correspondence of decision to condition)
N = hi + mi + fa + cr (by condition x decision)
mirt is the probability or rate of misses;
num contains basic numeric parameters;
init_num initializes basic numeric parameters;
freq contains current frequency information;
comp_freq computes current frequency information;
prob contains current probability information;
comp_prob computes current probability information;
is_freq verifies frequencies.
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