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authorjranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>2013-10-21 09:46:27 +0000
committerjranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb>2013-10-21 09:46:27 +0000
commit9b5f45d5f45722875adada2afc554cec8308a761 (patch)
tree2462f44c0ed2ecde3d8beb076d3328a613a96aba /R
parentff00631200c3ec1f0ca374b7204b199343717e15 (diff)
- Simplified implementation of mkinerrmin (see ChangeLog)
- Improve ChangeLog and add comment to source code - Simple test of the new mkinerrmin implementation in test.R - Added some summaries for documenting the changes in mkinerrmin git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@120 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
Diffstat (limited to 'R')
-rw-r--r--R/mkinerrmin.R15
1 files changed, 9 insertions, 6 deletions
diff --git a/R/mkinerrmin.R b/R/mkinerrmin.R
index 7d9d462..074cc56 100644
--- a/R/mkinerrmin.R
+++ b/R/mkinerrmin.R
@@ -22,16 +22,14 @@ if(getRversion() >= '2.15.1') utils::globalVariables(c("name", "value_mean"))
mkinerrmin <- function(fit, alpha = 0.05)
{
parms.optim <- fit$par
+
kinerrmin <- function(errdata, n.parms) {
means.mean <- mean(errdata$value_mean, na.rm = TRUE)
df = length(errdata$value_mean) - n.parms
- f <- function(err)
- {
- (sum((errdata$value_mean - errdata$value_pred)^2/((err * means.mean)^2)) -
- qchisq(1 - alpha,df))^2
- }
- err.min <- optimize(f, c(0.01,0.9))$minimum
+ err.min <- sqrt((1 / qchisq(1 - alpha, df)) *
+ sum((errdata$value_mean - errdata$value_pred)^2)/(means.mean^2))
+
return(list(err.min = err.min, n.optim = n.parms, df = df))
}
@@ -39,7 +37,12 @@ mkinerrmin <- function(fit, alpha = 0.05)
errdata <- merge(means, fit$predicted, by = c("time", "name"),
suffixes = c("_mean", "_pred"))
errdata <- errdata[order(errdata$time, errdata$name), ]
+
+ # Any value that is set to exactly zero is not really an observed value
+ # Remove those at time 0 - those are caused by the FOCUS recommendation
+ # to set metabolites occurring at time 0 to 0
errdata <- subset(errdata, !(time == 0 & value_mean == 0))
+
n.optim.overall <- length(parms.optim)
errmin.overall <- kinerrmin(errdata, n.optim.overall)

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