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,
abs_d_ppv_npv,
abs_d_sens_spec, accuracy,
cohens_kappa, cutpoint,
false_omission_rate,
misclassification_cost, npv,
odds_ratio, p_chisquared,
plr, precision,
prod_ppv_npv, prod_sens_spec,
recall, risk_ratio,
sensitivity, specificity,
sum_ppv_npv, sum_sens_spec,
total_utility, tpr,
tp, youden
# NOT RUN {
ppv(10, 5, 20, 10)
ppv(c(10, 8), c(5, 7), c(20, 12), c(10, 18))
# }
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