From 69504b635d388507bce650c44b3bfe17cad3383e Mon Sep 17 00:00:00 2001 From: ranke Date: Fri, 12 May 2006 21:59:33 +0000 Subject: - Fixed the inverse prediction - Now I have a working approach for the calculation of LOD and LOQ, but it seems to be different from what everybody else is doing (e.g. Massart chaper 13). I like it, however. Maybe it even yields a paper. git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@8 5fad18fb-23f0-0310-ab10-e59a3bee62b4 --- man/inverse.predict.Rd | 13 ++++++++----- 1 file changed, 8 insertions(+), 5 deletions(-) (limited to 'man/inverse.predict.Rd') diff --git a/man/inverse.predict.Rd b/man/inverse.predict.Rd index d773e58..8c2be9c 100644 --- a/man/inverse.predict.Rd +++ b/man/inverse.predict.Rd @@ -4,9 +4,8 @@ \alias{inverse.predict.rlm} \alias{inverse.predict.default} \title{Predict x from y for a linear calibration} -\usage{inverse.predict(object, newdata, - ws = ifelse(length(object$weights) > 0, mean(object$weights), 1), - alpha=0.05, ss = "auto") +\usage{inverse.predict(object, newdata, \dots, + ws, alpha=0.05, ss = "auto") } \arguments{ \item{object}{ @@ -17,12 +16,16 @@ \item{newdata}{ A vector of observed y values for one sample. } + \item{\dots}{ + Placeholder for further arguments that might be needed by + future implementations. + } \item{ws}{ The weight attributed to the sample. The default is to take the mean of the weights in the model, if there are any. } \item{alpha}{ - The confidence level for the confidence interval to be reported. + The error tolerance level for the confidence interval to be reported. } \item{ss}{ The estimated standard error of the sample measurements. The @@ -62,6 +65,6 @@ w <- round(1/(s^2),digits=3) weights <- w[factor(x)] m <- lm(y ~ x,w=weights) -inverse.predict(m,c(15)) +inverse.predict(m,15,ws = 1.67) } \keyword{manip} -- cgit v1.2.1