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-\name{din32645}
-\docType{data}
-\alias{din32645}
-\title{Calibration data from DIN 32645}
-\description{
- Sample dataset to test the package.
-}
-\usage{data(din32645)}
-\format{
- A dataframe containing 10 rows of x and y values.
-}
-\examples{
-data(din32645)
-m <- lm(y ~ x, data = din32645)
-calplot(m)
-
-## Prediction of x with confidence interval
-(prediction <- inverse.predict(m, 3500, alpha = 0.01))
-
-# This should give 0.07434 according to test data from Dintest, which
-# was collected from Procontrol 3.1 (isomehr GmbH) in this case
-round(prediction$Confidence,5)
-
-## Critical value:
-(crit <- lod(m, alpha = 0.01, beta = 0.5))
-
-# According to DIN 32645, we should get 0.07 for the critical value
-# (decision limit, "Nachweisgrenze")
-round(crit$x, 2)
-# and according to Dintest test data, we should get 0.0698 from
-round(crit$x, 4)
-
-## Limit of detection (smallest detectable value given alpha and beta)
-# In German, the smallest detectable value is the "Erfassungsgrenze", and we
-# should get 0.14 according to DIN, which we achieve by using the method
-# described in it:
-lod.din <- lod(m, alpha = 0.01, beta = 0.01, method = "din")
-round(lod.din$x, 2)
-
-## Limit of quantification
-# This accords to the test data coming with the test data from Dintest again,
-# except for the last digits of the value cited for Procontrol 3.1 (0.2121)
-(loq <- loq(m, alpha = 0.01))
-round(loq$x,4)
-
-# A similar value is obtained using the approximation
-# LQ = 3.04 * LC (Currie 1999, p. 120)
-3.04 * lod(m,alpha = 0.01, beta = 0.5)$x
-}
-\references{
- DIN 32645 (equivalent to ISO 11843), Beuth Verlag, Berlin, 1994
-
- Dintest. Plugin for MS Excel for evaluations of calibration data. Written
- by Georg Schmitt, University of Heidelberg.
- \url{http://www.rzuser.uni-heidelberg.de/~df6/download/dintest.htm}
-
- Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
- detection and quantification capabilities (IUPAC Recommendations 1995).
- Analytica Chimica Acta 391, 105 - 126.
-}
-\keyword{datasets}

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