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+\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 }
+}
+\value{
+  The standard deviation of the response variable.
+}
+\references{
+  Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
+  Additive, Multiplicative, and Mixed Analytical Errors. Clinical Chemistry
+  24(11), 1895-1898.
+
+  Rocke, David M. and Lorenzato, Stefan (1995) A two-component model for
+  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+}