From 0a3eb0893cb4bd1b12f07a79069d1c7f5e991495 Mon Sep 17 00:00:00 2001
From: Johannes Ranke <jranke@uni-bremen.de>
Date: Fri, 25 Oct 2019 00:37:42 +0200
Subject: Use roxygen for functions and methods

---
 man/sigma_twocomp.Rd | 41 ++++++++++++++++++++++++-----------------
 1 file changed, 24 insertions(+), 17 deletions(-)

(limited to 'man/sigma_twocomp.Rd')

diff --git a/man/sigma_twocomp.Rd b/man/sigma_twocomp.Rd
index 9e91fe78..3e7854f1 100644
--- a/man/sigma_twocomp.Rd
+++ b/man/sigma_twocomp.Rd
@@ -1,31 +1,38 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/sigma_twocomp.R
 \name{sigma_twocomp}
 \alias{sigma_twocomp}
 \title{Two component error model}
-\description{
-  Function describing the standard deviation of the measurement error 
-  in dependence of the measured value \eqn{y}:
-
-    \deqn{\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}}
-    {sigma = sqrt(sigma_low^2 + y^2 * rsd_high^2)}
-
-  This is the error model used for example by Werner et al. (1978). The model
-  proposed by Rocke and Lorenzato (1995) can be written in this form as well,
-  but assumes approximate lognormal distribution of errors for high values of y.
-}
 \usage{
 sigma_twocomp(y, sigma_low, rsd_high)
 }
 \arguments{
-  \item{y}{ The magnitude of the observed value } 
-  \item{sigma_low}{ The asymptotic minimum of the standard deviation for low observed values }
-  \item{rsd_high}{ The coefficient describing the increase of the standard deviation with 
-    the magnitude of the observed value }
+\item{y}{The magnitude of the observed value}
+
+\item{sigma_low}{The asymptotic minimum of the standard deviation for low
+observed values}
+
+\item{rsd_high}{The coefficient describing the increase of the standard
+deviation with the magnitude of the observed value}
 }
 \value{
-  The standard deviation of the response variable.
+The standard deviation of the response variable.
+}
+\description{
+Function describing the standard deviation of the measurement error in
+dependence of the measured value \eqn{y}:
+}
+\details{
+\deqn{\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}} sigma =
+sqrt(sigma_low^2 + y^2 * rsd_high^2)
+
+This is the error model used for example by Werner et al. (1978). The model
+proposed by Rocke and Lorenzato (1995) can be written in this form as well,
+but assumes approximate lognormal distribution of errors for high values of
+y.
 }
 \references{
-  Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
+Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
   Additive, Multiplicative, and Mixed Analytical Errors. Clinical Chemistry
   24(11), 1895-1898.
 
-- 
cgit v1.2.1