# fart

0th

Percentile

##### The false alarm rate (or false positive rate) of a decision process or diagnostic procedure.

fart defines a decision's false alarm rate (or the rate of false positives): The conditional probability of the decision being positive if the condition is FALSE.

Keywords
datasets
##### Usage
fart
##### Details

Understanding or obtaining the false alarm rate fart:

• Definition: fart is the conditional probability for an incorrect positive decision given that the condition is FALSE:

fart = p(decision = positive | condition = FALSE)

or the probability of a false alarm.

• Perspective: fart further classifies the subset of cond_false individuals by decision (fart = fa/cond_false).

• Alternative names: false positive rate (FPR), rate of type-I errors (alpha), statistical significance level, fallout

• Relationships:

a. fart is the complement of the specificity spec:

fart = 1 - spec

b. fart is the opposite conditional probability -- but not the complement -- of the false discovery rate or false detection rate FDR:

FDR = p(condition = FALSE | decision = positive)

• In terms of frequencies, fart is the ratio of fa divided by cond_false (i.e., fa + cr):

fart = fa/cond_false = fa/(fa + cr)

• Dependencies: fart is a feature of a decision process or diagnostic procedure and a measure of incorrect decisions (false positives).

However, due to being a conditional probability, the value of fart is not intrinsic to the decision process, but also depends on the condition's prevalence value prev.

##### Format

An object of class numeric of length 1.

##### References

comp_fart computes fart as the complement of spec prob contains current probability information; comp_prob computes current probability information; num contains basic numeric parameters; init_num initializes basic numeric parameters; comp_freq computes current frequency information; is_prob verifies probabilities.

Other probabilities: FDR, FOR, NPV, PPV, acc, err, mirt, ppod, prev, sens, spec

• fart
• FPR
• alpha
• fallout
##### Examples
# NOT RUN {
fart <- .25     # sets a false alarm rate of 25%
fart <- 25/100  # (decision = positive) for 25 out of 100 people with (condition = FALSE)
is_prob(fart)   # TRUE

# }

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

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