riskyr (version 0.1.0)

comp_acc: Compute overall accuracy (acc) from probabilities.

Description

comp_acc computes overall accuracy acc from 3 essential probabilities prev, sens, and spec.

Usage

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

See comp_accu and accu for accuracy metrics based on frequencies.

Details

comp_acc uses probabilities (not frequencies) as inputs and returns a proportion (probability) without rounding.

Definition: acc is the overall accuracy as the proportion (or probability) of correctly classifying cases or of dec.cor cases:

acc = dec.cor/N = (hi + cr)/(hi + mi + fa + cr)

Values range from 0 (no correct prediction) to 1 (perfect prediction).

Importantly, correct decisions dec.cor are not necessarily positive decisions dec.pos.

See Also

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, 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, comp_accu

Examples

# NOT RUN {
# ways to work:
comp_acc(.10, .200, .300)  # => acc = 0.29
comp_acc(.50, .333, .666)  # => acc = 0.4995

# watch out for vectors:
prev.range <- seq(0, 1, by = .1)
comp_acc(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_acc(1, 1, 1)  #  => 1
comp_acc(1, 1, 0)  #  => 1

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

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

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


# }