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authorJohannes Ranke <jranke@uni-bremen.de>2019-10-25 00:37:42 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2019-10-25 02:03:54 +0200
commit0a3eb0893cb4bd1b12f07a79069d1c7f5e991495 (patch)
tree1bf0ffeb710b3438fee224d0a657606b4c36b495 /man/sigma_twocomp.Rd
parent053bf27d3f265c7a7378e2df3e00cf891e0d1bb2 (diff)
Use roxygen for functions and methods
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1 files changed, 24 insertions, 17 deletions
diff --git a/man/sigma_twocomp.Rd b/man/sigma_twocomp.Rd
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--- 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.

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