# init_num

##### Initialize basic numeric variables.

`init_num`

initializes basic numeric variables to define `num`

as a list of named elements containing four basic probabilities
(`prev`

, `sens`

, `spec`

, and `fart`

)
and one frequency parameter (the population size `N`

).

##### Usage

```
init_num(prev = num.def$prev, sens = num.def$sens,
spec = num.def$spec, fart = num.def$fart, N = num.def$N)
```

##### Arguments

- prev
The condition's prevalence value

`prev`

(i.e., the probability of condition being`TRUE`

).- sens
The decision's sensitivity value

`sens`

(i.e., the conditional probability of a positive decision provided that the condition is`TRUE`

).- spec
The decision's specificity value

`spec`

(i.e., the conditional probability of a negative decision provided that the condition is`FALSE`

).`spec`

is optional when is complement`fart`

is provided.- fart
The decision's false alarm rate

`fart`

(i.e., the conditional probability of a positive decision provided that the condition is`FALSE`

).`fart`

is optional when its complement`spec`

is provided.- N
The population size

`N`

.

##### Details

If `spec`

is provided, its complement `fart`

is optional.
If `fart`

is provided, its complement `spec`

is optional.
If no `N`

is provided, a suitable minimum value is
computed by `comp_min_N`

.

##### Value

A list containing a valid quadruple of probabilities
(`prev`

, `sens`

,
`spec`

, and `fart`

)
and one frequency (population size `N`

).

##### See Also

`num`

contains basic numeric parameters;
`pal`

contains current color settings;
`txt`

contains current text settings;
`freq`

contains current frequency information;
`comp_freq`

computes frequencies from probabilities;
`prob`

contains current probability information;
`comp_prob`

computes current probability information;
`is_valid_prob_set`

verifies sets of probability inputs;
`is_extreme_prob_set`

verifies sets of extreme probabilities;
`comp_min_N`

computes a suitable minimum population size `N`

.

Other functions initializing scenario information: `init_pal`

,
`init_txt`

, `riskyr`

##### Examples

```
# NOT RUN {
# ways to succeed:
init_num(1, 1, 1, 0, 100) # => succeeds
init_num(1, 1, 0, 1, 100) # => succeeds
# watch out for:
init_num(1, 1, 0, 1) # => succeeds (with N computed)
init_num(1, 1, NA, 1, 100) # => succeeds (with spec computed)
init_num(1, 1, 0, NA, 100) # => succeeds (with fart computed)
init_num(1, 1, NA, 1) # => succeeds (with spec and N computed)
init_num(1, 1, 0, NA) # => succeeds (with fart and N computed)
init_num(1, 1, .51, .50, 100) # => succeeds (as spec and fart are within tolarated range)
# ways to fail:
init_num(prev = NA) # => NAs + warning (NA)
init_num(prev = 88) # => NAs + warning (beyond range)
init_num(prev = 1, sens = NA) # => NAs + warning (NA)
init_num(prev = 1, sens = 1, spec = NA, fart = NA) # => NAs + warning (NAs)
init_num(1, 1, .52, .50, 100) # => NAs + warning (complements beyond range)
# }
```

*Documentation reproduced from package riskyr, version 0.2.0, License: GPL-2 | GPL-3*