`mi`

is the frequency of misses
or false negatives (`FN`

)
in a population of `N`

individuals.

`mi`

An object of class `numeric`

of length 1.

Definition:
`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.

Relationships:

to probabilities: The frequency

`mi`

depends on the miss rate`mirt`

(aka. false negative rate, FNR) and is conditional on the prevalence`prev`

.to other frequencies: In a population of size

`N`

the following relationships hold:

`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.

Other essential parameters: `cr`

,
`fa`

, `hi`

, `prev`

,
`sens`

, `spec`

Other frequencies: `N`

,
`cond_false`

, `cond_true`

,
`cr`

, `dec_cor`

,
`dec_err`

, `dec_neg`

,
`dec_pos`

, `fa`

, `hi`