Calculate the positive predictive value (PPV) from
true positives, false positives, true negatives and false negatives.
The inputs must be vectors of equal length.
ppv = tp / (tp + fp)
ppv(tp, fp, tn, fn, ...)(numeric) number of true positives.
(numeric) number of false positives.
(numeric) number of true negatives.
(numeric) number of false negatives.
for capturing additional arguments passed by method.
Other metric functions:
F1_score(),
Jaccard(),
abs_d_ppv_npv(),
abs_d_sens_spec(),
accuracy(),
cohens_kappa(),
cutpoint(),
false_omission_rate(),
metric_constrain(),
misclassification_cost(),
npv(),
odds_ratio(),
p_chisquared(),
plr(),
precision(),
prod_ppv_npv(),
prod_sens_spec(),
recall(),
risk_ratio(),
roc01(),
sensitivity(),
specificity(),
sum_ppv_npv(),
sum_sens_spec(),
total_utility(),
tp(),
tpr(),
youden()
ppv(10, 5, 20, 10)
ppv(c(10, 8), c(5, 7), c(20, 12), c(10, 18))
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