https://github.com/cran/cutpointr
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Tip revision: 2900dc24d2c5a7d8fdb3f1abb1540fb704e51742 authored by Christian Thiele on 15 February 2021, 13:40:03 UTC
version 1.1.0
Tip revision: 2900dc2
sum_ppv_npv.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/metrics.R
\name{sum_ppv_npv}
\alias{sum_ppv_npv}
\title{Calculate the sum of positive and negative predictive value}
\usage{
sum_ppv_npv(tp, fp, tn, fn, ...)
}
\arguments{
\item{tp}{(numeric) number of true positives.}

\item{fp}{(numeric) number of false positives.}

\item{tn}{(numeric) number of true negatives.}

\item{fn}{(numeric) number of false negatives.}

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