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
prod_sens_spec.Rd
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/metrics.R
\name{prod_sens_spec}
\alias{prod_sens_spec}
\title{Calculate the product of sensitivity and specificity}
\usage{
prod_sens_spec(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 product of sensitivity and specificity from
true positives, false positives, true negatives and false negatives.
The inputs must be vectors of equal length. \cr \cr
sensitivity = tp / (tp + fn) \cr
specificity = tn / (tn + fp) \cr
prod_sens_spec = sensitivity * specificity \cr
}
\examples{
prod_sens_spec(10, 5, 20, 10)
prod_sens_spec(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{recall}}, \code{\link{risk_ratio}},
  \code{\link{roc01}}, \code{\link{sensitivity}},
  \code{\link{specificity}}, \code{\link{sum_ppv_npv}},
  \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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