R/comp_prob_prob.R
comp_FDR.Rdcomp_FDR(prev, sens, spec)The condition's prevalence prev
(i.e., the probability of condition being TRUE).
The decision's sensitivity sens
(i.e., the conditional probability of a positive decision
provided that the condition is TRUE).
The decision's specificity value spec
(i.e., the conditional probability
of a negative decision provided that the condition is FALSE).
The false detection rate FDR as a probability.
A warning is provided for NaN values.
comp_FDR uses probabilities (not frequencies)
and does not round results.
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_FOR(),
comp_NPV(),
comp_PPV(),
comp_accu_freq(),
comp_accu_prob(),
comp_acc(),
comp_comp_pair(),
comp_complement(),
comp_complete_prob_set(),
comp_err(),
comp_fart(),
comp_mirt(),
comp_ppod(),
comp_prob_freq(),
comp_prob(),
comp_sens(),
comp_spec()
# (1) Ways to work:
comp_FDR(.50, .500, .500) # => FDR = 0.5 = (1 - PPV)
#> [1] 0.5
comp_FDR(.50, .333, .666) # => FDR = 0.5007 = (1 - PPV)
#> [1] 0.5007496