1 files changed, 7 insertions, 14 deletions
diff --git a/R/sigma_twocomp.R b/R/sigma_twocomp.R
index e8a92ced..e7f4368b 100644
--- a/R/sigma_twocomp.R
+++ b/R/sigma_twocomp.R
@@ -1,16 +1,16 @@
 #' 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
@@ -20,7 +20,7 @@
 #' @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.
 #' @examples
@@ -36,15 +36,8 @@
 #'   data = d_syn, na.action = na.omit,
 #'   start = list(parent_0 = 100, lrc = -3))
 #' if (length(findFunction("varConstProp")) > 0) {
-#'   f_gnls_tc <- gnls(value ~ SSasymp(time, 0, parent_0, lrc),
-#'     data = d_syn, na.action = na.omit,
-#'     start = list(parent_0 = 100, lrc = -3),
-#'     weights = varConstProp())
-#'   f_gnls_tc_sf <- gnls(value ~ SSasymp(time, 0, parent_0, lrc),
-#'     data = d_syn, na.action = na.omit,
-#'     start = list(parent_0 = 100, lrc = -3),
-#'     control = list(sigma = 1),
-#'     weights = varConstProp())
+#'   f_gnls_tc <- update(f_gnls, weights = varConstProp())
+#'   f_gnls_tc_sf <- update(f_gnls_tc, control = list(sigma = 1))
 #' }
 #' f_mkin <- mkinfit("SFO", d_syn, error_model = "const", quiet = TRUE)
 #' f_mkin_tc <- mkinfit("SFO", d_syn, error_model = "tc", quiet = TRUE)