From a6694c655fde246dd4d59b44fd10b22738b3fb08 Mon Sep 17 00:00:00 2001
From: jranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>
Date: Mon, 7 May 2012 18:51:46 +0000
Subject: - Moved the call to mkinerrmin to summary.mkinfit - The argument to
 mkinerrmin is now an object of class mkinfit - Fixed the allocation of
 parameters to observed variables in mkinerrmin

git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@37 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
---
 man/mkinerrmin.Rd  | 25 ++++++++++++-------------
 man/mkinpredict.Rd |  2 +-
 2 files changed, 13 insertions(+), 14 deletions(-)

(limited to 'man')

diff --git a/man/mkinerrmin.Rd b/man/mkinerrmin.Rd
index 654115b..c43d87a 100644
--- a/man/mkinerrmin.Rd
+++ b/man/mkinerrmin.Rd
@@ -10,30 +10,29 @@ smallest relative error still resulting in passing the chi-squared test
 as defined in the FOCUS kinetics report from 2006.
 }
 \usage{
-mkinerrmin(errdata, n.parms, alpha = 0.05)
+mkinerrmin(fit, alpha = 0.05)
 }
 \arguments{
-  \item{errdata}{
-    A data frame with mean observed values in column named \code{value_mean}
-    and predicted values in column \code{value_pred}.
-}
-  \item{n.parms}{
-    The number of optimized parameters to be taken into account for the data series.
-}
+  \item{fit}{
+    an object of class \code{\link{mkinfit}}.
+  }
   \item{alpha}{
     The confidence level chosen for the chi-squared test.
 }
 }
 \value{
-  A list with the following components:
+  A dataframe with the following components:
   \item{err.min}{The relative error, expressed as a fraction.}
   \item{n.optim}{The number of optimised parameters attributed to the data series.}
-  \item{df}{The number of remaining degrees of freedom for the chi2 error level calculations.
-    Note that mean values are used for the chi2 statistic and therefore every time point with 
-    observed values in the series only counts one time.}
+  \item{df}{The number of remaining degrees of freedom for the chi2 error level
+    calculations.  Note that mean values are used for the chi2 statistic and
+    therefore every time point with observed values in the series only counts
+    one time.}
+  The dataframe has one row for the total dataset and one further row for
+  each observed state variable in the model.
 }
 \details{
-    This function is used internally by \code{\link{mkinfit}}.
+    This function is used internally by \code{\link{summary.mkinfit}}.
 }
 \references{ 
   FOCUS (2006) \dQuote{Guidance Document on Estimating Persistence and
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index aaa77e6..d293144 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -60,7 +60,7 @@ mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve", map_
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 1:20, solution_type = "analytical")[20,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, atol = 1e-20)[20,]
   # The integration method does not make a lot of difference
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, atol = 1e-20, method = "bdf")[20,]
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, atol = 1e-20, method = "ode45")[20,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, atol = 1e-20, method = "rk4")[20,]
   # The number of output times does make a lot of difference
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), seq(0, 20, by = 0.1))[201,]
-- 
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