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author | Johannes Ranke <jranke@uni-bremen.de> | 2019-10-25 00:37:42 +0200 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2019-10-25 02:03:54 +0200 |
commit | 0a3eb0893cb4bd1b12f07a79069d1c7f5e991495 (patch) | |
tree | 1bf0ffeb710b3438fee224d0a657606b4c36b495 /man/sigma_twocomp.Rd | |
parent | 053bf27d3f265c7a7378e2df3e00cf891e0d1bb2 (diff) |
Use roxygen for functions and methods
Diffstat (limited to 'man/sigma_twocomp.Rd')
-rw-r--r-- | man/sigma_twocomp.Rd | 41 |
1 files changed, 24 insertions, 17 deletions
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. |