https://github.com/cran/cutpointr
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Tip revision: 62a2af802192e86b60cc64dfd458d581a064c0c7 authored by Christian Thiele on 13 April 2018, 12:16:17 UTC
version 0.7.3
Tip revision: 62a2af8
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{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{sensitivity}},
  \code{\link{specificity}}, \code{\link{sum_sens_spec}},
  \code{\link{total_utility}}, \code{\link{tpr}},
  \code{\link{tp}}, \code{\link{youden}}
}
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