`comp_complete_prob_set`

is a function takes a
valid set of (3 to 5) probabilities as inputs (as a vector)
and returns the complete set of
(3 essential and 2 optional) probabilities.

comp_complete_prob_set(prev, sens = NA, mirt = NA, spec = NA,
fart = NA)

## Arguments

prev |
The condition's prevalence `prev`
(i.e., the probability of condition being `TRUE` ). |

sens |
The decision's sensitivity `sens`
(i.e., the conditional probability of a positive decision
provided that the condition is `TRUE` ).
`sens` is optional when its complement `mirt` is provided. |

mirt |
The decision's miss rate `mirt`
(i.e., the conditional probability of a negative decision
provided that the condition is `TRUE` ).
`mirt` is optional when its complement `sens` is provided. |

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 its 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. |

## Value

A vector of 5 probabilities:
`c(prev, sens, mirt, spec, fart)`

.

## Details

Assuming that `is_valid_prob_set = TRUE`

this function uses `comp_comp_pair`

on the
two optional pairs (i.e.,
`sens`

and `mirt`

, and
`spec`

and `fart`

) and
returns the complete set of 5 probabilities.

## See also

`is_valid_prob_set`

verifies a set of probability inputs;
`is_extreme_prob_set`

verifies extreme cases;
`comp_comp_pair`

computes pairs of complements;
`is_complement`

verifies numeric complements;
`is_prob`

verifies probabilities;
`comp_prob`

computes current probability information;
`prob`

contains current probability information;
`init_num`

initializes basic numeric variables;
`num`

contains basic numeric variables.

Other functions computing probabilities: `comp_FDR`

,
`comp_FOR`

, `comp_NPV`

,
`comp_PPV`

, `comp_accu_freq`

,
`comp_accu_prob`

, `comp_acc`

,
`comp_comp_pair`

,
`comp_complement`

, `comp_err`

,
`comp_fart`

, `comp_mirt`

,
`comp_ppod`

, `comp_prob_freq`

,
`comp_prob`

, `comp_sens`

,
`comp_spec`

## Examples

# ways to work:
comp_complete_prob_set(1, .8, NA, .7, NA) # => 1.0 0.8 0.2 0.7 0.3

#> [1] 1.0 0.8 0.2 0.7 0.3

comp_complete_prob_set(1, NA, .8, NA, .4) # => 1.0 0.2 0.8 0.6 0.4

#> [1] 1.0 0.2 0.8 0.6 0.4

# watch out for:
comp_complete_prob_set(8) # => 8 NA NA NA NA + warnings

#> Warning: One argument (either p1 or p2) is necessary.

#> Warning: One argument (either p1 or p2) is necessary.

#> [1] 8 NA NA NA NA

comp_complete_prob_set(8, 7, 6, 5, 4) # => 8 7 6 5 4 + no warning (valid set assumed)

#> [1] 8 7 6 5 4

comp_complete_prob_set(8, .8, NA, .7, NA) # => 8.0 0.8 0.2 0.7 0.3 + no warning (sic)

#> [1] 8.0 0.8 0.2 0.7 0.3

comp_complete_prob_set(8, 2, NA, 3, NA) # => 8 2 NA 3 NA + no warning (sic)

#> [1] 8 2 NA 3 NA