From 6865f34bfe02ceae7027fcb0bc7d074d84369cf1 Mon Sep 17 00:00:00 2001
From: ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4>
Date: Mon, 1 Oct 2007 19:48:47 +0000
Subject: Further work on the new repository layout

git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@23 5fad18fb-23f0-0310-ab10-e59a3bee62b4
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-\name{loq}
-\alias{loq}
-\alias{loq.lm}
-\alias{loq.rlm}
-\alias{loq.default}
-\title{Estimate a limit of quantification (LOQ)}
-\usage{
-  loq(object, \dots, alpha = 0.05, k = 3, n = 1, w.loq = "auto",
-    var.loq = "auto")
-}
-\arguments{
-  \item{object}{
-    A univariate model object of class \code{\link{lm}} or 
-    \code{\link[MASS:rlm]{rlm}} 
-    with model formula \code{y ~ x} or \code{y ~ x - 1}, 
-    optionally from a weighted regression. If weights are specified
-    in the model, either \code{w.loq} or \code{var.loq} have to 
-    be specified.
-  }
-  \item{alpha}{
-    The error tolerance for the prediction of x values in the calculation.
-  }
-  \item{\dots}{
-    Placeholder for further arguments that might be needed by 
-    future implementations.
-  }
-  \item{k}{ 
-    The inverse of the maximum relative error tolerated at the
-    desired LOQ.
-  }
-  \item{n}{
-    The number of replicate measurements for which the LOQ should be
-    specified.
-  }
-  \item{w.loq}{
-    The weight that should be attributed to the LOQ. Defaults
-    to one for unweighted regression, and to the mean of the weights
-    for weighted regression. See \code{\link{massart97ex3}} for 
-    an example how to take advantage of knowledge about the 
-    variance function.
-  }
-  \item{var.loq}{
-    The approximate variance at the LOQ. The default value is 
-    calculated from the model.
-  }
-}
-\value{
-  The estimated limit of quantification for a model used for calibration.
-}
-\description{
-  The limit of quantification is the x value, where the relative error
-  of the quantification given the calibration model reaches a prespecified
-  value 1/k. Thus, it is the solution of the equation
-    \deqn{L = k c(L)}{L = k * c(L)}
-  where c(L) is half of the length of the confidence interval at the limit L
-  (DIN 32645, equivalent to ISO 11843). c(L) is internally estimated by
-  \code{\link{inverse.predict}}, and L is obtained by iteration. 
-}
-\note{
-  - IUPAC recommends to base the LOQ on the standard deviation of the signal
-    where x = 0. 
-  - The calculation of a LOQ based on weighted regression is non-standard
-    and therefore not tested. Feedback is welcome.
-}
-\examples{
-data(massart97ex3)
-attach(massart97ex3)
-m <- lm(y ~ x)
-loq(m)
-
-# We can get better by using replicate measurements
-loq(m, n = 3)
-}
-\seealso{
-  Examples for \code{\link{din32645}}  
-}
-\keyword{manip}
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