diff options
Diffstat (limited to 'man')
| -rw-r--r-- | man/calplot.lm.Rd | 26 | ||||
| -rw-r--r-- | man/chemCal-package.Rd | 8 | ||||
| -rw-r--r-- | man/lod.Rd | 3 | ||||
| -rw-r--r-- | man/massart97ex3.Rd | 14 |
4 files changed, 31 insertions, 20 deletions
diff --git a/man/calplot.lm.Rd b/man/calplot.lm.Rd index 734933d..de63022 100644 --- a/man/calplot.lm.Rd +++ b/man/calplot.lm.Rd @@ -8,8 +8,9 @@ as prediction and confidence bands. } \usage{ - calplot(object, xlim = "auto", ylim = "auto", - xlab = "Concentration", ylab = "Response", alpha=0.05) + calplot(object, xlim = c("auto","auto"), ylim = c("auto","auto"), + xlab = "Concentration", ylab = "Response", alpha=0.05, + varfunc = NULL) } \arguments{ \item{object}{ @@ -32,22 +33,25 @@ \item{alpha}{ The error tolerance level for the confidence and prediction bands. } + \item{varfunc}{ + The variance function for generating the weights in the model. + Currently, this argument is ignored (see note below). + } } \value{ A plot of the calibration data, of your fitted model as well as lines showing the confidence limits as well as the prediction limits. } +\note{ + Prediction bands for models from weighted linear regression require weights + for the data, for which responses should be predicted. Prediction intervals + for weighted models are not currently supported by the internally used + function \code{\link{predict.lm}}, therefore, \code{calplot} refuses to work + for such models. +} \examples{ -# Example of a Calibration plot for a weighted regression -source("/home/ranke/tmp/r-base-2.3.0/src/library/stats/R/lm.R") data(massart97ex3) -attach(massart97ex3) -yx <- split(y,factor(x)) -s <- round(sapply(yx,sd),digits=2) -w <- round(1/(s^2),digits=3) -weights <- w[factor(x)] -m <- lm(y ~ x,w=10 * weights) -calplot(m) +m <- lm(y ~ x, data=massart97ex3) calplot(m) } \author{ diff --git a/man/chemCal-package.Rd b/man/chemCal-package.Rd index a11744e..4456150 100644 --- a/man/chemCal-package.Rd +++ b/man/chemCal-package.Rd @@ -2,16 +2,16 @@ \alias{chemCal-package} \docType{package} \title{ -Calibration functions for analytical chemistry + Calibration functions for analytical chemistry } \description{ -See \url{../DESCRIPTION} + See \url{../DESCRIPTION} } \details{ -There is a package vignette located in \url{../doc/chemCal.pdf}. + There is a package vignette located in \url{../doc/chemCal.pdf}. } \author{ -Author and Maintainer: Johannes Ranke <jranke@uni-bremen.de> + Author and Maintainer: Johannes Ranke <jranke@uni-bremen.de> } \keyword{manip} } @@ -43,6 +43,9 @@ - The estimation of the LOD in terms of the analyte amount/concentration xD from the LOD in the signal domain SD is done by simply inverting the calibration function (i.e. assuming a known calibration function). + - The calculation of a LOD from weighted calibration models requires + a weights argument for the internally used \code{\link{predict.lm}} + function, which is currently not supported in R. } \references{ Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., diff --git a/man/massart97ex3.Rd b/man/massart97ex3.Rd index 2618709..eb00e79 100644 --- a/man/massart97ex3.Rd +++ b/man/massart97ex3.Rd @@ -23,18 +23,22 @@ m <- lm(y ~ x,w=weights) inverse.predict(m, 15, ws = 1.67) inverse.predict(m, 90, ws = 0.145) -calplot(m) +# Some of the following examples are commented out, because the require +# prediction intervals from predict.lm for weighted models, which is not +# available in R at the moment. + +#calplot(m) m0 <- lm(y ~ x) lod(m0) -lod(m) +#lod(m) # Now we want to take advantage of the lower weights at lower y values -m2 <- lm(y ~ x, w = 1/y) +#m2 <- lm(y ~ x, w = 1/y) # To get a reasonable weight for the lod, we need to estimate it and predict # a y value for it -yhat.lod <- predict(m,data.frame(x = lod(m2))) -lod(m2,w=1/yhat.lod,k=3) +#yhat.lod <- predict(m,data.frame(x = lod(m2))) +#lod(m2,w=1/yhat.lod,k=3) } \source{ Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., |