`comp_err`

computes overall error rate `err`

from 3 essential probabilities
`prev`

, `sens`

, and `spec`

.

comp_err(prev, sens, spec)

## 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` ). |

spec |
The decision's specificity value `spec`
(i.e., the conditional probability
of a negative decision provided that the condition is `FALSE` ). |

## Value

Overall error rate `err`

as a probability (proportion).
A warning is provided for NaN values.

## Details

`comp_err`

uses `comp_acc`

to
compute `err`

as the
complement of `acc`

:

`err = 1 - acc`

See `comp_acc`

and `acc`

for further details and
`accu`

for other accuracy metrics
and several possible interpretations of accuracy.

## See also

`comp_acc`

computes overall accuracy `acc`

from probabilities;
`accu`

lists all accuracy metrics;
`comp_accu_prob`

computes exact accuracy metrics from probabilities;
`comp_accu_freq`

computes accuracy metrics from frequencies;
`comp_sens`

and `comp_PPV`

compute related probabilities;
`is_extreme_prob_set`

verifies extreme cases;
`comp_complement`

computes a probability's complement;
`is_complement`

verifies probability complements;
`comp_prob`

computes current probability information;
`prob`

contains current probability information;
`is_prob`

verifies probabilities.

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_complete_prob_set`

,
`comp_fart`

, `comp_mirt`

,
`comp_ppod`

, `comp_prob_freq`

,
`comp_prob`

, `comp_sens`

,
`comp_spec`

Other metrics: `accu`

, `acc`

,
`comp_accu_freq`

,
`comp_accu_prob`

, `comp_acc`

,
`err`

## Examples

# ways to work:
comp_err(.10, .200, .300) # => err = 0.71

#> [1] 0.71

comp_err(.50, .333, .666) # => err = 0.5005

#> [1] 0.5005

#> [1] 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5

# watch out for extreme values:
comp_err(1, 1, 1) # => 0

#> [1] 0

comp_err(1, 1, 0) # => 0

#> [1] 0

comp_err(1, 0, 1) # => 1

#> [1] 1

comp_err(1, 0, 0) # => 1

#> [1] 1

comp_err(0, 1, 1) # => 0

#> [1] 0

comp_err(0, 1, 0) # => 1

#> [1] 1

comp_err(0, 0, 1) # => 0

#> [1] 0

comp_err(0, 0, 0) # => 1

#> [1] 1