Use roxygen for functions and methods

1 files changed, 26 insertions, 0 deletions

diff --git a/R/sigma_twocomp.R b/R/sigma_twocomp.R
index b06816c1..c9a15aa8 100644
--- a/R/sigma_twocomp.R
+++ b/R/sigma_twocomp.R
@@ -1,3 +1,29 @@
+#' Two component error model
+#' 
+#' 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.
+#' 
+#' @param y The magnitude of the observed value
+#' @param sigma_low The asymptotic minimum of the standard deviation for low
+#'   observed values
+#' @param rsd_high The coefficient describing the increase of the standard
+#'   deviation with the magnitude of the observed value
+#' @return 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.
+#' @export
   sigma_twocomp <- function(y, sigma_low, rsd_high) {
     sqrt(sigma_low^2 + y^2 * rsd_high^2)
   }