# comp_err

##### Compute overall error rate (err) from probabilities.

`comp_err`

computes overall error rate `err`

from 3 essential probabilities
`prev`

, `sens`

, and `spec`

.

##### Usage

`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`

).

##### 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.

##### Value

Overall error rate `err`

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

##### 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

```
# NOT RUN {
# ways to work:
comp_err(.10, .200, .300) # => err = 0.71
comp_err(.50, .333, .666) # => err = 0.5005
# watch out for vectors:
prev.range <- seq(0, 1, by = .1)
comp_err(prev.range, .5, .5) # => 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
comp_err(1, 1, 0) # => 0
comp_err(1, 0, 1) # => 1
comp_err(1, 0, 0) # => 1
comp_err(0, 1, 1) # => 0
comp_err(0, 1, 0) # => 1
comp_err(0, 0, 1) # => 0
comp_err(0, 0, 0) # => 1
# }
```

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