https://github.com/cran/cutpointr
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Tip revision: 030e7096a6bb7c391a35b49ac6eea87ad3b6027a authored by Christian Thiele on 17 September 2019, 20:30:02 UTC
version 1.0.0
Tip revision: 030e709
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{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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