Fix URLs in README, convert to roxygenv0.2.3

- The roxygen conversion was done using Rd2roxygen
- Also edit _pkgdown.yml to group the reference
- Use markdown bullet lists for lod and loq docs

39 files changed, 1192 insertions, 532 deletions

diff --git a/.Rbuildignore b/.Rbuildignore
index 3115cf6..f0b4d3d 100644
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -4,6 +4,7 @@ check.log$
 chemCal_.*.tar.gz
 docs
 _pkgdown.yml
+README.rmd
 README.html
 .travis.yml
 experimental
diff --git a/DESCRIPTION b/DESCRIPTION
index cbf3c38..806d3d5 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -20,4 +20,4 @@ VignetteBuilder: knitr
 Encoding: UTF-8
 BugReports: https://github.com/jranke/chemCal/issues
 URL: https://pkgdown.jrwb.de/chemCal/, https://cgit.jrwb.de/chemCal/about
-RoxygenNote: 6.1.1
+RoxygenNote: 7.1.2
diff --git a/NAMESPACE b/NAMESPACE
index 7ca061a..5f98a2a 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -1,14 +1,22 @@
-# Export all names
-exportPattern(".")
-S3method(calplot, default)
-S3method(calplot, lm)
-S3method(lod, default)
-S3method(lod, lm)
-S3method(loq, default)
-S3method(loq, lm)
-S3method(inverse.predict, default)
-S3method(inverse.predict, lm)
-S3method(inverse.predict, rlm)
+# Generated by roxygen2: do not edit by hand
 
-importFrom("graphics", "legend", "matlines", "plot", "points")
-importFrom("stats", "optimize", "predict", "qt")
+S3method(calplot,default)
+S3method(calplot,lm)
+S3method(inverse.predict,default)
+S3method(inverse.predict,lm)
+S3method(inverse.predict,rlm)
+S3method(lod,default)
+S3method(lod,lm)
+S3method(loq,default)
+S3method(loq,lm)
+export(calplot)
+export(inverse.predict)
+export(lod)
+export(loq)
+importFrom(graphics,legend)
+importFrom(graphics,matlines)
+importFrom(graphics,plot)
+importFrom(graphics,points)
+importFrom(stats,optimize)
+importFrom(stats,predict)
+importFrom(stats,qt)
diff --git a/R/calplot.R b/R/calplot.R
index fd49a54..3c227d4 100644
--- a/R/calplot.R
+++ b/R/calplot.R
@@ -1,3 +1,45 @@
+#' Plot calibration graphs from univariate linear models
+#' 
+#' Produce graphics of calibration data, the fitted model as well as
+#' confidence, and, for unweighted regression, prediction bands.
+#' 
+#' @aliases calplot calplot.default calplot.lm
+#' @param 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}.
+#' @param xlim The limits of the plot on the x axis.
+#' @param ylim The limits of the plot on the y axis.
+#' @param xlab The label of the x axis.
+#' @param ylab The label of the y axis.
+#' @param legend_x An optional numeric value for adjusting the x coordinate of
+#' the legend.
+#' @param alpha The error tolerance level for the confidence and prediction
+#' bands. Note that this includes both tails of the Gaussian distribution,
+#' unlike the alpha and beta parameters used in \code{\link{lod}} (see note
+#' below).
+#' @param varfunc The variance function for generating the weights in the
+#' model.  Currently, this argument is ignored (see note below).
+#' @return A plot of the calibration data, of your fitted model as well as
+#' lines showing the confidence limits. Prediction limits are only shown for
+#' models from unweighted regression.
+#' @note Prediction bands for models from weighted linear regression require
+#' weights for the data, for which responses should be predicted. Prediction
+#' intervals using weights e.g. from a variance function are currently not
+#' supported by the internally used function \code{\link{predict.lm}},
+#' therefore, \code{calplot} does not draw prediction bands for such models.
+#' 
+#' It is possible to compare the \code{\link{calplot}} prediction bands with
+#' the \code{\link{lod}} values if the \code{lod()} alpha and beta parameters
+#' are half the value of the \code{calplot()} alpha parameter.
+#' @author Johannes Ranke
+#' @importFrom graphics legend matlines plot points
+#' @examples
+#' 
+#' data(massart97ex3)
+#' m <- lm(y ~ x, data = massart97ex3)
+#' calplot(m)
+#' 
+#' @export calplot
 calplot <- function(object, 
   xlim = c("auto", "auto"), ylim = c("auto", "auto"), 
   xlab = "Concentration", ylab = "Response",
@@ -7,6 +49,7 @@ calplot <- function(object,
   UseMethod("calplot")
 }
 
+#' @export
 calplot.default <- function(object, 
   xlim = c("auto","auto"), ylim = c("auto","auto"), 
   xlab = "Concentration", ylab = "Response",
@@ -16,6 +59,7 @@ calplot.default <- function(object,
   stop("Calibration plots only implemented for univariate lm objects.")
 }
 
+#' @export
 calplot.lm <- function(object,
   xlim = c("auto","auto"), ylim = c("auto","auto"), 
   xlab = "Concentration", ylab = "Response",
diff --git a/R/chemCal-package.R b/R/chemCal-package.R
new file mode 100644
index 0000000..8cc8c76
--- /dev/null
+++ b/R/chemCal-package.R
@@ -0,0 +1,194 @@
+#' Calibration data from DIN 32645
+#' 
+#' Sample dataset to test the package.
+#' 
+#' 
+#' @name din32645
+#' @docType data
+#' @format A dataframe containing 10 rows of x and y values.
+#' @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. Formerly available from the Website
+#' of the University of Heidelberg.
+#' 
+#' Currie, L. A. (1997) Nomenclature in evaluation of analytical methods
+#' including detection and quantification capabilities (IUPAC Recommendations
+#' 1995).  Analytica Chimica Acta 391, 105 - 126.
+#' @keywords datasets
+#' @examples
+#' 
+#' 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
+#' 
+NULL
+
+
+
+
+
+#' Calibration data from Massart et al. (1997), example 1
+#' 
+#' Sample dataset from p. 175 to test the package.
+#' 
+#' 
+#' @name massart97ex1
+#' @docType data
+#' @format A dataframe containing 6 observations of x and y data.
+#' @source Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S.,
+#' Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+#' Qualimetrics: Part A, Chapter 8.
+#' @keywords datasets
+NULL
+
+
+
+
+
+#' Calibration data from Massart et al. (1997), example 3
+#' 
+#' Sample dataset from p. 188 to test the package.
+#' 
+#' 
+#' @name massart97ex3
+#' @docType data
+#' @format A dataframe containing 6 levels of x values with 5 observations of y
+#' for each level.
+#' @source Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S.,
+#' Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+#' Qualimetrics: Part A, Chapter 8.
+#' @keywords datasets
+#' @examples
+#' 
+#' # For reproducing the results for replicate standard measurements in example 8,
+#' # we need to do the calibration on the means when using chemCal > 0.2
+#' weights <- with(massart97ex3, {
+#'   yx <- split(y, x)
+#'   ybar <- sapply(yx, mean)
+#'   s <- round(sapply(yx, sd), digits = 2)
+#'   w <- round(1 / (s^2), digits = 3)
+#' })
+#' 
+#' massart97ex3.means <- aggregate(y ~ x, massart97ex3, mean)
+#' 
+#' m3.means <- lm(y ~ x, w = weights, data = massart97ex3.means)
+#' 
+#' # The following concords with the book p. 200
+#' inverse.predict(m3.means, 15, ws = 1.67)  # 5.9 +- 2.5
+#' inverse.predict(m3.means, 90, ws = 0.145) # 44.1 +- 7.9
+#' 
+#' # The LOD is only calculated for models from unweighted regression
+#' # with this version of chemCal
+#' m0 <- lm(y ~ x, data = massart97ex3) 
+#' lod(m0)
+#' 
+#' # Limit of quantification from unweighted regression
+#' loq(m0)
+#' 
+#' # For calculating the limit of quantification from a model from weighted
+#' # regression, we need to supply weights, internally used for inverse.predict
+#' # If we are not using a variance function, we can use the weight from
+#' # the above example as a first approximation (x = 15 is close to our
+#' # loq approx 14 from above).
+#' loq(m3.means, w.loq = 1.67)
+#' # The weight for the loq should therefore be derived at x = 7.3 instead
+#' # of 15, but the graphical procedure of Massart (p. 201) to derive the 
+#' # variances on which the weights are based is quite inaccurate anyway. 
+#' 
+NULL
+
+
+
+
+
+#' Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato
+#' (1995)
+#' 
+#' Dataset reproduced from Table 1 in Rocke and Lorenzato (1995).
+#' 
+#' 
+#' @name rl95_cadmium
+#' @docType data
+#' @format A dataframe containing four replicate observations for each of the
+#' six calibration standards.
+#' @source Rocke, David M. und Lorenzato, Stefan (1995) A two-component model
+#' for measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+#' @keywords datasets
+NULL
+
+
+
+
+
+#' Toluene amounts measured by GC/MS as reported by Rocke and Lorenzato (1995)
+#' 
+#' Dataset reproduced from Table 4 in Rocke and Lorenzato (1995). The toluene
+#' amount in the calibration samples is given in picograms per 100 µL.
+#' Presumably this is the volume that was injected into the instrument.
+#' 
+#' 
+#' @name rl95_toluene
+#' @docType data
+#' @format A dataframe containing four replicate observations for each of the
+#' six calibration standards.
+#' @source Rocke, David M. und Lorenzato, Stefan (1995) A two-component model
+#' for measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+#' @keywords datasets
+NULL
+
+
+
+
+
+#' Example data for calibration with replicates from University of Toronto
+#' 
+#' Dataset read into R from
+#' \url{https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls}.
+#' 
+#' 
+#' @name utstats14
+#' @docType data
+#' @format A tibble containing three replicate observations of the response for
+#' five calibration concentrations.
+#' @source David Stone and Jon Ellis (2011) Statistics in Analytical Chemistry.
+#' Tutorial website maintained by the Departments of Chemistry, University of
+#' Toronto.
+#' \url{https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html}
+#' @keywords datasets
+NULL
+
+
+
diff --git a/R/inverse.predict.lm.R b/R/inverse.predict.lm.R
index 77d548f..031f9d4 100644
--- a/R/inverse.predict.lm.R
+++ b/R/inverse.predict.lm.R
@@ -1,19 +1,87 @@
-# This is an implementation of Equation (8.28) in the Handbook of Chemometrics
-# and Qualimetrics, Part A, Massart et al (1997), page 200, validated with
-# Example 8 on the same page, extended as specified in the package vignette
-
+#' Predict x from y for a linear calibration
+#' 
+#' This function predicts x values using a univariate linear model that has
+#' been generated for the purpose of calibrating a measurement method.
+#' Prediction intervals are given at the specified confidence level.  The
+#' calculation method was taken from Massart et al. (1997). In particular,
+#' Equations 8.26 and 8.28 were combined in order to yield a general treatment
+#' of inverse prediction for univariate linear models, taking into account
+#' weights that have been used to create the linear model, and at the same time
+#' providing the possibility to specify a precision in sample measurements
+#' differing from the precision in standard samples used for the calibration.
+#' This is elaborated in the package vignette.
+#'
+#' This is an implementation of Equation (8.28) in the Handbook of Chemometrics
+#' and Qualimetrics, Part A, Massart et al (1997), page 200, validated with
+#' Example 8 on the same page, extended as specified in the package vignette
+#' 
+#' @aliases inverse.predict inverse.predict.lm inverse.predict.rlm
+#' inverse.predict.default
+#' @param 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}.
+#' @param newdata A vector of observed y values for one sample.
+#' @param \dots Placeholder for further arguments that might be needed by
+#' future implementations.
+#' @param ws The weight attributed to the sample. This argument is obligatory
+#' if \code{object} has weights.
+#' @param alpha The error tolerance level for the confidence interval to be
+#' reported.
+#' @param var.s The estimated variance of the sample measurements. The default
+#' is to take the residual standard error from the calibration and to adjust it
+#' using \code{ws}, if applicable. This means that \code{var.s} overrides
+#' \code{ws}.
+#' @return A list containing the predicted x value, its standard error and a
+#' confidence interval.
+#' @note The function was validated with examples 7 and 8 from Massart et al.
+#' (1997).  Note that the behaviour of inverse.predict changed with chemCal
+#' version 0.2.1. Confidence intervals for x values obtained from calibrations
+#' with replicate measurements did not take the variation about the means into
+#' account.  Please refer to the vignette for details.
+#' @references Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong,
+#' S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+#' Qualimetrics: Part A, p. 200
+#' @importFrom stats optimize predict qt
+#' @examples
+#' 
+#' # This is example 7 from Chapter 8 in Massart et al. (1997)
+#' m <- lm(y ~ x, data = massart97ex1)
+#' inverse.predict(m, 15)        #  6.1 +- 4.9
+#' inverse.predict(m, 90)        # 43.9 +- 4.9
+#' inverse.predict(m, rep(90,5)) # 43.9 +- 3.2
+#' 
+#' # For reproducing the results for replicate standard measurements in example 8,
+#' # we need to do the calibration on the means when using chemCal > 0.2
+#' weights <- with(massart97ex3, {
+#'   yx <- split(y, x)
+#'   ybar <- sapply(yx, mean)
+#'   s <- round(sapply(yx, sd), digits = 2)
+#'   w <- round(1 / (s^2), digits = 3)
+#' })
+#' 
+#' massart97ex3.means <- aggregate(y ~ x, massart97ex3, mean)
+#' 
+#' m3.means <- lm(y ~ x, w = weights, data = massart97ex3.means)
+#' 
+#' inverse.predict(m3.means, 15, ws = 1.67)  # 5.9 +- 2.5
+#' inverse.predict(m3.means, 90, ws = 0.145) # 44.1 +- 7.9
+#' 
+#' 
+#' @export
 inverse.predict <- function(object, newdata, ...,
   ws = "auto", alpha = 0.05, var.s = "auto")
 {
   UseMethod("inverse.predict")
 }
 
+#' @export
 inverse.predict.default <- function(object, newdata, ...,
   ws = "auto", alpha = 0.05, var.s = "auto")
 {
   stop("Inverse prediction only implemented for univariate lm objects.")
 }
 
+#' @export
 inverse.predict.lm <- function(object, newdata, ...,
   ws = "auto", alpha = 0.05, var.s = "auto")
 {
@@ -31,6 +99,7 @@ inverse.predict.lm <- function(object, newdata, ...,
     ws = ws, alpha = alpha, var.s = var.s, w = w, xname = xname, yname = yname)
 }
 
+#' @export
 inverse.predict.rlm <- function(object, newdata, ...,
   ws = "auto", alpha = 0.05, var.s = "auto")
 {
diff --git a/R/lod.R b/R/lod.R
index bccdf3e..bf6e928 100644
--- a/R/lod.R
+++ b/R/lod.R
@@ -1,13 +1,74 @@
+#' Estimate a limit of detection (LOD)
+#' 
+#' The decision limit (German: Nachweisgrenze) is defined as the signal or
+#' analyte concentration that is significantly different from the blank signal
+#' with a first order error alpha (one-sided significance test).  The detection
+#' limit, or more precise, the minimum detectable value (German:
+#' Erfassungsgrenze), is then defined as the signal or analyte concentration
+#' where the probability that the signal is not detected although the analyte
+#' is present (type II or false negative error), is beta (also a one-sided
+#' significance test).
+#' 
+#' @aliases lod lod.lm lod.rlm lod.default
+#' @param 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.
+#' @param \dots Placeholder for further arguments that might be needed by
+#' future implementations.
+#' @param alpha The error tolerance for the decision limit (critical value).
+#' @param beta The error tolerance beta for the detection limit.
+#' @param method The \dQuote{default} method uses a prediction interval at the
+#' LOD for the estimation of the LOD, which obviously requires iteration. This
+#' is described for example in Massart, p. 432 ff.  The \dQuote{din} method
+#' uses the prediction interval at x = 0 as an approximation.
+#' @param tol When the \dQuote{default} method is used, the default tolerance
+#' for the LOD on the x scale is the value of the smallest non-zero standard
+#' divided by 1000. Can be set to a numeric value to override this.
+#' @return A list containig the corresponding x and y values of the estimated
+#' limit of detection of a model used for calibration.
+#' @note 
+#' * The default values for alpha and beta are the ones recommended by IUPAC.
+#' * 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.
+#' @seealso Examples for \code{\link{din32645}}
+#' @references Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong,
+#' S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+#' Qualimetrics: Part A, Chapter 13.7.8
+#' 
+#' J. Inczedy, T. Lengyel, and A.M. Ure (2002) International Union of Pure and
+#' Applied Chemistry Compendium of Analytical Nomenclature: Definitive Rules.
+#' Web edition.
+#' 
+#' Currie, L. A. (1997) Nomenclature in evaluation of analytical methods
+#' including detection and quantification capabilities (IUPAC Recommendations
+#' 1995).  Analytica Chimica Acta 391, 105 - 126.
+#' @importFrom stats optimize predict
+#' @examples
+#' 
+#' m <- lm(y ~ x, data = din32645)
+#' lod(m) 
+#' 
+#' # The critical value (decision limit, German Nachweisgrenze) can be obtained
+#' # by using beta = 0.5:
+#' lod(m, alpha = 0.01, beta = 0.5)
+#' 
+#' @export
 lod <- function(object, ..., alpha = 0.05, beta = 0.05, method = "default", tol = "default")
 {
   UseMethod("lod")
 }
 
+#' @export
 lod.default <- function(object, ..., alpha = 0.05, beta = 0.05, method = "default", tol = "default")
 {
   stop("lod is only implemented for univariate lm objects.")
 }
 
+#' @export
 lod.lm <- function(object, ..., alpha = 0.05, beta = 0.05, method = "default", tol = "default")
 {
   if (length(object$weights) > 0) {
diff --git a/R/loq.R b/R/loq.R
index 26d6a53..a4dbcfe 100644
--- a/R/loq.R
+++ b/R/loq.R
@@ -1,15 +1,65 @@
+#' Estimate a limit of quantification (LOQ)
+#' 
+#' 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.
+#' 
+#' @aliases loq loq.lm loq.rlm loq.default
+#' @param 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.
+#' @param alpha The error tolerance for the prediction of x values in the
+#' calculation.
+#' @param \dots Placeholder for further arguments that might be needed by
+#' future implementations.
+#' @param k The inverse of the maximum relative error tolerated at the desired
+#' LOQ.
+#' @param n The number of replicate measurements for which the LOQ should be
+#' specified.
+#' @param 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.
+#' @param var.loq The approximate variance at the LOQ. The default value is
+#' calculated from the model.
+#' @param tol The default tolerance for the LOQ on the x scale is the value of
+#' the smallest non-zero standard divided by 1000. Can be set to a numeric
+#' value to override this.
+#' @return The estimated limit of quantification for a model used for
+#' calibration.
+#' @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.
+#' @seealso Examples for \code{\link{din32645}}
+#' @examples
+#' 
+#' m <- lm(y ~ x, data = massart97ex1)
+#' loq(m)
+#' 
+#' # We can get better by using replicate measurements
+#' loq(m, n = 3)
+#' 
+#' @export
 loq <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto", 
   var.loq = "auto", tol = "default")
 {
   UseMethod("loq")
 }
 
+#' @export
 loq.default <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto",
   var.loq = "auto", tol = "default")
 {
   stop("loq is only implemented for univariate lm objects.")
 }
 
+#' @export
 loq.lm <- function(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto",
   var.loq = "auto", tol = "default")
 {
diff --git a/README.html b/README.html
index 47ce3a1..3bb6cbd 100644
--- a/README.html
+++ b/README.html
@@ -611,7 +611,7 @@ body {
 <h2 id="overview">Overview</h2>
 <p>chemCal is an R package providing some basic functions for conveniently working with linear calibration curves with one explanatory variable.</p>
 <h2 id="installation">Installation</h2>
-<p>From within <a href="https://r-project.org">R</a>, get the official chemCal release using</p>
+<p>From within <a href="https://www.r-project.org/">R</a>, get the official chemCal release using</p>
 <div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true"></a><span class="kw">install.packages</span>(<span class="st">&quot;chemCal&quot;</span>)</span></code></pre></div>
 <h2 id="usage">Usage</h2>
 <p>chemCal works with univariate linear models of class <code>lm</code>. Working with one of the datasets coming with chemCal, we can produce a calibration plot using the <code>calplot</code> function:</p>
@@ -671,7 +671,7 @@ body {
 <span id="cb7-11"><a href="#cb7-11" aria-hidden="true"></a><span class="co">#&gt; $`Confidence Limits`</span></span>
 <span id="cb7-12"><a href="#cb7-12" aria-hidden="true"></a><span class="co">#&gt; [1] 42.30749 45.57217</span></span></code></pre></div>
 <h2 id="reference">Reference</h2>
-<p>You can use the R help system to view documentation, or you can have a look at the <a href="https://pkgdown.jrwb.de/chemCal">online documentation</a>.</p>
+<p>You can use the R help system to view documentation, or you can have a look at the <a href="https://pkgdown.jrwb.de/chemCal/">online documentation</a>.</p>
 
 </body>
 </html>
diff --git a/README.md b/README.md
index 2ad063e..b7b4db6 100644
--- a/README.md
+++ b/README.md
@@ -139,5 +139,5 @@ inverse.predict(m0, c(91, 89, 87, 93, 90))
 You can use the R help system to view documentation, or you can
 have a look at the [online documentation][pd-site].
 
-[r-project]: https://r-project.org
-[pd-site]: https://pkgdown.jrwb.de/chemCal
+[r-project]: https://www.r-project.org/
+[pd-site]: https://pkgdown.jrwb.de/chemCal/
diff --git a/README.rmd b/README.rmd
index 6b027f4..361b4c0 100644
--- a/README.rmd
+++ b/README.rmd
@@ -99,5 +99,5 @@ inverse.predict(m0, c(91, 89, 87, 93, 90))
 You can use the R help system to view documentation, or you can
 have a look at the [online documentation][pd-site].
 
-[r-project]: https://r-project.org
-[pd-site]: https://pkgdown.jrwb.de/chemCal
+[r-project]: https://www.r-project.org/
+[pd-site]: https://pkgdown.jrwb.de/chemCal/
diff --git a/_pkgdown.yml b/_pkgdown.yml
index f5eeff8..7942085 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -2,3 +2,19 @@ title: chemCal
 
 template:
   bootswatch: spacelab
+
+reference:
+  - title: Main functions
+    contents:
+      - calplot
+      - lod
+      - loq
+      - inverse.predict
+  - title: Datasets
+    contents:
+      - din32645
+      - massart97ex1
+      - massart97ex3
+      - rl95_cadmium
+      - rl95_toluene
+      - utstats14
diff --git a/docs/articles/chemCal.html b/docs/articles/chemCal.html
index 4e145bf..bbcc568 100644
--- a/docs/articles/chemCal.html
+++ b/docs/articles/chemCal.html
@@ -98,7 +98,7 @@
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/chemCal/" class="external-link">chemCal</a></span><span class="op">)</span>
 <span class="va">m0</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex3</span><span class="op">)</span>
-<span class="fu"><a href="../reference/calplot.lm.html">calplot</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="../reference/calplot.html">calplot</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></code></pre></div>
 <p><img src="chemCal_files/figure-html/unnamed-chunk-1-1.png" width="700"></p>
 <p>As we can see, the scatter increases with increasing x. This is also illustrated by one of the diagnostic plots for linear models provided by R:</p>
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
diff --git a/docs/index.html b/docs/index.html
index 4019484..7882a73 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -87,7 +87,7 @@
 <div class="section level2">
 <h2 id="installation">Installation<a class="anchor" aria-label="anchor" href="#installation"></a>
 </h2>
-<p>From within <a href="https://r-project.org" class="external-link">R</a>, get the official chemCal release using</p>
+<p>From within <a href="https://www.r-project.org/" class="external-link">R</a>, get the official chemCal release using</p>
 <div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span class="fu"><a href="https://rdrr.io/r/utils/install.packages.html" class="external-link">install.packages</a></span><span class="op">(</span><span class="st">"chemCal"</span><span class="op">)</span></code></pre></div>
 </div>
@@ -101,7 +101,7 @@
 <div class="sourceCode" id="cb2"><pre class="downlit sourceCode r">
 <code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://pkgdown.jrwb.de/chemCal/" class="external-link">chemCal</a></span><span class="op">)</span>
 <span class="va">m0</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex3</span><span class="op">)</span>
-<span class="fu"><a href="reference/calplot.lm.html">calplot</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></code></pre></div>
+<span class="fu"><a href="reference/calplot.html">calplot</a></span><span class="op">(</span><span class="va">m0</span><span class="op">)</span></code></pre></div>
 <p><img src="reference/figures/README-calplot-1.png"><!-- --></p>
 </div>
 <div class="section level3">
@@ -169,7 +169,7 @@
 <div class="section level2">
 <h2 id="reference">Reference<a class="anchor" aria-label="anchor" href="#reference"></a>
 </h2>
-<p>You can use the R help system to view documentation, or you can have a look at the <a href="https://pkgdown.jrwb.de/chemCal" class="external-link">online documentation</a>.</p>
+<p>You can use the R help system to view documentation, or you can have a look at the <a href="https://pkgdown.jrwb.de/chemCal/" class="external-link">online documentation</a>.</p>
 </div>
 </div>
   </div>
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index dc4cced..3c1d018 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -3,5 +3,5 @@ pkgdown: 2.0.2
 pkgdown_sha: ~
 articles:
   chemCal: chemCal.html
-last_built: 2022-03-31T16:32Z
+last_built: 2022-03-31T17:56Z
 
diff --git a/docs/reference/calplot-1.png b/docs/reference/calplot-1.png
new file mode 100644
index 0000000..c2deae8
--- /dev/null
+++ b/docs/reference/calplot-1.png
diff --git a/docs/reference/calplot.html b/docs/reference/calplot.html
new file mode 100644
index 0000000..88321b1
--- /dev/null
+++ b/docs/reference/calplot.html
@@ -0,0 +1,154 @@
+<!DOCTYPE html>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Plot calibration graphs from univariate linear models — calplot • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Plot calibration graphs from univariate linear models — calplot"><meta property="og:description" content="Produce graphics of calibration data, the fitted model as well as
+confidence, and, for unweighted regression, prediction bands."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
+<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
+<![endif]--></head><body data-spy="scroll" data-target="#toc">
+    
+
+    <div class="container template-reference-topic">
+      <header><div class="navbar navbar-default navbar-fixed-top" role="navigation">
+  <div class="container">
+    <div class="navbar-header">
+      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false">
+        <span class="sr-only">Toggle navigation</span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+        <span class="icon-bar"></span>
+      </button>
+      <span class="navbar-brand">
+        <a class="navbar-link" href="../index.html">chemCal</a>
+        <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="">0.2.3</span>
+      </span>
+    </div>
+
+    <div id="navbar" class="navbar-collapse collapse">
+      <ul class="nav navbar-nav"><li>
+  <a href="../articles/chemCal.html">Get started</a>
+</li>
+<li>
+  <a href="../reference/index.html">Reference</a>
+</li>
+<li>
+  <a href="../news/index.html">Changelog</a>
+</li>
+      </ul><ul class="nav navbar-nav navbar-right"><li>
+  <a href="https://github.com/jranke/chemCal/" class="external-link">
+    <span class="fab fa-github fa-lg"></span>
+     
+  </a>
+</li>
+      </ul></div><!--/.nav-collapse -->
+  </div><!--/.container -->
+</div><!--/.navbar -->
+
+      
+
+      </header><div class="row">
+  <div class="col-md-9 contents">
+    <div class="page-header">
+    <h1>Plot calibration graphs from univariate linear models</h1>
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/calplot.R" class="external-link"><code>R/calplot.R</code></a></small>
+    <div class="hidden name"><code>calplot.Rd</code></div>
+    </div>
+
+    <div class="ref-description">
+    <p>Produce graphics of calibration data, the fitted model as well as
+confidence, and, for unweighted regression, prediction bands.</p>
+    </div>
+
+    <div id="ref-usage">
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">calplot</span><span class="op">(</span>
+  <span class="va">object</span>,
+  xlim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"auto"</span><span class="op">)</span>,
+  ylim <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"auto"</span><span class="op">)</span>,
+  xlab <span class="op">=</span> <span class="st">"Concentration"</span>,
+  ylab <span class="op">=</span> <span class="st">"Response"</span>,
+  legend_x <span class="op">=</span> <span class="st">"auto"</span>,
+  alpha <span class="op">=</span> <span class="fl">0.05</span>,
+  varfunc <span class="op">=</span> <span class="cn">NULL</span>
+<span class="op">)</span></code></pre></div>
+    </div>
+
+    <div id="arguments">
+    <h2>Arguments</h2>
+    <dl><dt>object</dt>
+<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or
+<code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> with model formula <code>y ~ x</code> or <code>y ~ x -
+1</code>.</p></dd>
+<dt>xlim</dt>
+<dd><p>The limits of the plot on the x axis.</p></dd>
+<dt>ylim</dt>
+<dd><p>The limits of the plot on the y axis.</p></dd>
+<dt>xlab</dt>
+<dd><p>The label of the x axis.</p></dd>
+<dt>ylab</dt>
+<dd><p>The label of the y axis.</p></dd>
+<dt>legend_x</dt>
+<dd><p>An optional numeric value for adjusting the x coordinate of
+the legend.</p></dd>
+<dt>alpha</dt>
+<dd><p>The error tolerance level for the confidence and prediction
+bands. Note that this includes both tails of the Gaussian distribution,
+unlike the alpha and beta parameters used in <code><a href="lod.html">lod</a></code> (see note
+below).</p></dd>
+<dt>varfunc</dt>
+<dd><p>The variance function for generating the weights in the
+model.  Currently, this argument is ignored (see note below).</p></dd>
+</dl></div>
+    <div id="value">
+    <h2>Value</h2>
+    <p>A plot of the calibration data, of your fitted model as well as
+lines showing the confidence limits. Prediction limits are only shown for
+models from unweighted regression.</p>
+    </div>
+    <div id="note">
+    <h2>Note</h2>
+    <p>Prediction bands for models from weighted linear regression require
+weights for the data, for which responses should be predicted. Prediction
+intervals using weights e.g. from a variance function are currently not
+supported by the internally used function <code><a href="https://rdrr.io/r/stats/predict.lm.html" class="external-link">predict.lm</a></code>,
+therefore, <code>calplot</code> does not draw prediction bands for such models.</p>
+<p>It is possible to compare the <code>calplot</code> prediction bands with
+the <code><a href="lod.html">lod</a></code> values if the <code><a href="lod.html">lod()</a></code> alpha and beta parameters
+are half the value of the <code>calplot()</code> alpha parameter.</p>
+    </div>
+    <div id="author">
+    <h2>Author</h2>
+    <p>Johannes Ranke</p>
+    </div>
+
+    <div id="ref-examples">
+    <h2>Examples</h2>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span>
+<span class="r-in"><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">massart97ex3</span><span class="op">)</span></span>
+<span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex3</span><span class="op">)</span></span>
+<span class="r-in"><span class="fu">calplot</span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span>
+<span class="r-plt img"><img src="calplot-1.png" alt="" width="700" height="433"></span>
+<span class="r-in"></span>
+</code></pre></div>
+    </div>
+  </div>
+  <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar">
+    <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2>
+    </nav></div>
+</div>
+
+
+      <footer><div class="copyright">
+  <p></p><p>Developed by Johannes Ranke.</p>
+</div>
+
+<div class="pkgdown">
+  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p>
+</div>
+
+      </footer></div>
+
+  
+
+
+  
+
+  </body></html>
+
diff --git a/docs/reference/din32645.html b/docs/reference/din32645.html
index 1c02f36..ba6246a 100644
--- a/docs/reference/din32645.html
+++ b/docs/reference/din32645.html
@@ -47,7 +47,7 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Calibration data from DIN 32645</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/chemCal-package.R" class="external-link"><code>R/chemCal-package.R</code></a></small>
     <div class="hidden name"><code>din32645.Rd</code></div>
     </div>
 
@@ -55,9 +55,6 @@
     <p>Sample dataset to test the package.</p>
     </div>
 
-    <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">din32645</span><span class="op">)</span></code></pre></div>
-    </div>
 
     <div id="format">
     <h2>Format</h2>
@@ -66,18 +63,19 @@
     <div id="references">
     <h2>References</h2>
     <p>DIN 32645 (equivalent to ISO 11843), Beuth Verlag, Berlin, 1994</p>
-<p>Dintest. Plugin for MS Excel for evaluations of calibration data. Written
-  by Georg Schmitt, University of Heidelberg. Formerly available from
-  the Website of the University of Heidelberg.</p>
-<p>Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
-  detection and quantification capabilities (IUPAC Recommendations 1995). 
-  Analytica Chimica Acta 391, 105 - 126.</p>
+<p>Dintest. Plugin for MS Excel for evaluations of calibration data. Written by
+Georg Schmitt, University of Heidelberg. Formerly available from the Website
+of the University of Heidelberg.</p>
+<p>Currie, L. A. (1997) Nomenclature in evaluation of analytical methods
+including detection and quantification capabilities (IUPAC Recommendations
+1995).  Analytica Chimica Acta 391, 105 - 126.</p>
     </div>
 
     <div id="ref-examples">
     <h2>Examples</h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">din32645</span><span class="op">)</span></span>
-<span class="r-in"><span class="fu"><a href="calplot.lm.html">calplot</a></span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span>
+<span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">din32645</span><span class="op">)</span></span>
+<span class="r-in"><span class="fu"><a href="calplot.html">calplot</a></span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span>
 <span class="r-plt img"><img src="din32645-1.png" alt="" width="700" height="433"></span>
 <span class="r-in"></span>
 <span class="r-in"><span class="co">## Prediction of x with confidence interval</span></span>
@@ -118,6 +116,7 @@
 <span class="r-in"><span class="co"># LQ = 3.04 * LC (Currie 1999, p. 120)</span></span>
 <span class="r-in"><span class="fl">3.04</span> <span class="op">*</span> <span class="fu"><a href="lod.html">lod</a></span><span class="op">(</span><span class="va">m</span>, alpha <span class="op">=</span> <span class="fl">0.01</span>, beta <span class="op">=</span> <span class="fl">0.5</span><span class="op">)</span><span class="op">$</span><span class="va">x</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.2122306</span>
+<span class="r-in"></span>
 </code></pre></div>
     </div>
   </div>
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 3685007..9812256 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -50,22 +50,14 @@
     </div>
 
     <table class="ref-index"><colgroup><col class="alias"><col class="title"></colgroup><tbody><tr><th colspan="2">
-          <h2 id="all-functions">All functions <a href="#all-functions" class="anchor" aria-hidden="true"></a></h2>
+          <h2 id="main-functions">Main functions <a href="#main-functions" class="anchor" aria-hidden="true"></a></h2>
           <p class="section-desc"></p>
         </th>
       </tr></tbody><tbody><tr><td>
-          <p><code><a href="calplot.lm.html">calplot()</a></code> </p>
+          <p><code><a href="calplot.html">calplot()</a></code> </p>
         </td>
         <td><p>Plot calibration graphs from univariate linear models</p></td>
       </tr><tr><td>
-          <p><code><a href="din32645.html">din32645</a></code> </p>
-        </td>
-        <td><p>Calibration data from DIN 32645</p></td>
-      </tr><tr><td>
-          <p><code><a href="inverse.predict.html">inverse.predict()</a></code> </p>
-        </td>
-        <td><p>Predict x from y for a linear calibration</p></td>
-      </tr><tr><td>
           <p><code><a href="lod.html">lod()</a></code> </p>
         </td>
         <td><p>Estimate a limit of detection (LOD)</p></td>
@@ -74,6 +66,18 @@
         </td>
         <td><p>Estimate a limit of quantification (LOQ)</p></td>
       </tr><tr><td>
+          <p><code><a href="inverse.predict.html">inverse.predict()</a></code> </p>
+        </td>
+        <td><p>Predict x from y for a linear calibration</p></td>
+      </tr></tbody><tbody><tr><th colspan="2">
+          <h2 id="datasets">Datasets <a href="#datasets" class="anchor" aria-hidden="true"></a></h2>
+          <p class="section-desc"></p>
+        </th>
+      </tr></tbody><tbody><tr><td>
+          <p><code><a href="din32645.html">din32645</a></code> </p>
+        </td>
+        <td><p>Calibration data from DIN 32645</p></td>
+      </tr><tr><td>
           <p><code><a href="massart97ex1.html">massart97ex1</a></code> </p>
         </td>
         <td><p>Calibration data from Massart et al. (1997), example 1</p></td>
@@ -84,7 +88,8 @@
       </tr><tr><td>
           <p><code><a href="rl95_cadmium.html">rl95_cadmium</a></code> </p>
         </td>
-        <td><p>Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato (1995)</p></td>
+        <td><p>Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato
+(1995)</p></td>
       </tr><tr><td>
           <p><code><a href="rl95_toluene.html">rl95_toluene</a></code> </p>
         </td>
diff --git a/docs/reference/inverse.predict.html b/docs/reference/inverse.predict.html
index cb9fe98..6fe081e 100644
--- a/docs/reference/inverse.predict.html
+++ b/docs/reference/inverse.predict.html
@@ -1,14 +1,14 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Predict x from y for a linear calibration — inverse.predict • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Predict x from y for a linear calibration — inverse.predict"><meta property="og:description" content="This function predicts x values using a univariate linear model that has been
-  generated for the purpose of calibrating a measurement method. Prediction
-  intervals are given at the specified confidence level.
-  The calculation method was taken from Massart et al. (1997). In particular,
-  Equations 8.26 and 8.28 were combined in order to yield a general treatment
-  of inverse prediction for univariate linear models, taking into account 
-  weights that have been used to create the linear model, and at the same
-  time providing the possibility to specify a precision in sample measurements
-  differing from the precision in standard samples used for the calibration.
-  This is elaborated in the package vignette."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Predict x from y for a linear calibration — inverse.predict • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Predict x from y for a linear calibration — inverse.predict"><meta property="og:description" content="This function predicts x values using a univariate linear model that has
+been generated for the purpose of calibrating a measurement method.
+Prediction intervals are given at the specified confidence level.  The
+calculation method was taken from Massart et al. (1997). In particular,
+Equations 8.26 and 8.28 were combined in order to yield a general treatment
+of inverse prediction for univariate linear models, taking into account
+weights that have been used to create the linear model, and at the same time
+providing the possibility to specify a precision in sample measurements
+differing from the precision in standard samples used for the calibration.
+This is elaborated in the package vignette."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--></head><body data-spy="scroll" data-target="#toc">
@@ -56,73 +56,87 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Predict x from y for a linear calibration</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/inverse.predict.lm.R" class="external-link"><code>R/inverse.predict.lm.R</code></a></small>
     <div class="hidden name"><code>inverse.predict.Rd</code></div>
     </div>
 
     <div class="ref-description">
-    <p>This function predicts x values using a univariate linear model that has been
-  generated for the purpose of calibrating a measurement method. Prediction
-  intervals are given at the specified confidence level.
-  The calculation method was taken from Massart et al. (1997). In particular,
-  Equations 8.26 and 8.28 were combined in order to yield a general treatment
-  of inverse prediction for univariate linear models, taking into account 
-  weights that have been used to create the linear model, and at the same
-  time providing the possibility to specify a precision in sample measurements
-  differing from the precision in standard samples used for the calibration.
-  This is elaborated in the package vignette.</p>
+    <p>This function predicts x values using a univariate linear model that has
+been generated for the purpose of calibrating a measurement method.
+Prediction intervals are given at the specified confidence level.  The
+calculation method was taken from Massart et al. (1997). In particular,
+Equations 8.26 and 8.28 were combined in order to yield a general treatment
+of inverse prediction for univariate linear models, taking into account
+weights that have been used to create the linear model, and at the same time
+providing the possibility to specify a precision in sample measurements
+differing from the precision in standard samples used for the calibration.
+This is elaborated in the package vignette.</p>
     </div>
 
     <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">inverse.predict</span><span class="op">(</span><span class="va">object</span>, <span class="va">newdata</span>, <span class="va">...</span>,
-  <span class="va">ws</span>, alpha<span class="op">=</span><span class="fl">0.05</span>, var.s <span class="op">=</span> <span class="st">"auto"</span><span class="op">)</span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">inverse.predict</span><span class="op">(</span>
+  <span class="va">object</span>,
+  <span class="va">newdata</span>,
+  <span class="va">...</span>,
+  ws <span class="op">=</span> <span class="st">"auto"</span>,
+  alpha <span class="op">=</span> <span class="fl">0.05</span>,
+  var.s <span class="op">=</span> <span class="st">"auto"</span>
+<span class="op">)</span></code></pre></div>
     </div>
 
     <div id="arguments">
     <h2>Arguments</h2>
     <dl><dt>object</dt>
-<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or 
-    <code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> 
-    with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>.</p></dd>
+<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or
+<code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> with model formula <code>y ~ x</code> or <code>y ~ x -
+1</code>.</p></dd>
 <dt>newdata</dt>
 <dd><p>A vector of observed y values for one sample.</p></dd>
 <dt>...</dt>
-<dd><p>Placeholder for further arguments that might be needed by 
-    future implementations.</p></dd>
+<dd><p>Placeholder for further arguments that might be needed by
+future implementations.</p></dd>
 <dt>ws</dt>
 <dd><p>The weight attributed to the sample. This argument is obligatory
-    if <code>object</code> has weights.</p></dd>
+if <code>object</code> has weights.</p></dd>
 <dt>alpha</dt>
-<dd><p>The error tolerance level for the confidence interval to be reported.</p></dd>
+<dd><p>The error tolerance level for the confidence interval to be
+reported.</p></dd>
 <dt>var.s</dt>
-<dd><p>The estimated variance of the sample measurements. The default is to take
-    the residual standard error from the calibration and to adjust it
-    using <code>ws</code>, if applicable. This means that <code>var.s</code>
-    overrides <code>ws</code>.</p></dd>
+<dd><p>The estimated variance of the sample measurements. The default
+is to take the residual standard error from the calibration and to adjust it
+using <code>ws</code>, if applicable. This means that <code>var.s</code> overrides
+<code>ws</code>.</p></dd>
 </dl></div>
     <div id="value">
     <h2>Value</h2>
     <p>A list containing the predicted x value, its standard error and a
-  confidence interval.</p>
+confidence interval.</p>
+    </div>
+    <div id="details">
+    <h2>Details</h2>
+    <p>This is an implementation of Equation (8.28) in the Handbook of Chemometrics
+and Qualimetrics, Part A, Massart et al (1997), page 200, validated with
+Example 8 on the same page, extended as specified in the package vignette</p>
     </div>
     <div id="note">
     <h2>Note</h2>
-    <p>The function was validated with examples 7 and 8 from Massart et al. (1997). 
-  Note that the behaviour of inverse.predict changed with chemCal version
-  0.2.1. Confidence intervals for x values obtained from calibrations with
-  replicate measurements did not take the variation about the means into account.
-  Please refer to the vignette for details.</p>
+    <p>The function was validated with examples 7 and 8 from Massart et al.
+(1997).  Note that the behaviour of inverse.predict changed with chemCal
+version 0.2.1. Confidence intervals for x values obtained from calibrations
+with replicate measurements did not take the variation about the means into
+account.  Please refer to the vignette for details.</p>
     </div>
     <div id="references">
     <h2>References</h2>
-    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  p. 200</p>
+    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong,
+S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, p. 200</p>
     </div>
 
     <div id="ref-examples">
     <h2>Examples</h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># This is example 7 from Chapter 8 in Massart et al. (1997)</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span>
+<span class="r-in"><span class="co"># This is example 7 from Chapter 8 in Massart et al. (1997)</span></span>
 <span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex1</span><span class="op">)</span></span>
 <span class="r-in"><span class="fu">inverse.predict</span><span class="op">(</span><span class="va">m</span>, <span class="fl">15</span><span class="op">)</span>        <span class="co">#  6.1 +- 4.9</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $Prediction</span>
@@ -204,6 +218,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 36.20523 51.91526</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
 <span class="r-in"></span>
+<span class="r-in"></span>
 </code></pre></div>
     </div>
   </div>
diff --git a/docs/reference/lod.html b/docs/reference/lod.html
index a2d66ce..1fbae76 100644
--- a/docs/reference/lod.html
+++ b/docs/reference/lod.html
@@ -1,12 +1,12 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Estimate a limit of detection (LOD) — lod • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Estimate a limit of detection (LOD) — lod"><meta property="og:description" content="The decision limit (German: Nachweisgrenze) is defined as the signal or
-  analyte concentration that is significantly different from the blank signal
-  with a first order error alpha (one-sided significance test).
-  The detection limit, or more precise, the minimum detectable value 
-  (German: Erfassungsgrenze), is then defined as the signal or analyte
-  concentration where the probability that the signal is not detected although
-  the analyte is present (type II or false negative error), is beta (also a
-  one-sided significance test)."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+analyte concentration that is significantly different from the blank signal
+with a first order error alpha (one-sided significance test).  The detection
+limit, or more precise, the minimum detectable value (German:
+Erfassungsgrenze), is then defined as the signal or analyte concentration
+where the probability that the signal is not detected although the analyte
+is present (type II or false negative error), is beta (also a one-sided
+significance test)."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--></head><body data-spy="scroll" data-target="#toc">
@@ -54,76 +54,81 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Estimate a limit of detection (LOD)</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/lod.R" class="external-link"><code>R/lod.R</code></a></small>
     <div class="hidden name"><code>lod.Rd</code></div>
     </div>
 
     <div class="ref-description">
     <p>The decision limit (German: Nachweisgrenze) is defined as the signal or
-  analyte concentration that is significantly different from the blank signal
-  with a first order error alpha (one-sided significance test).
-  The detection limit, or more precise, the minimum detectable value 
-  (German: Erfassungsgrenze), is then defined as the signal or analyte
-  concentration where the probability that the signal is not detected although
-  the analyte is present (type II or false negative error), is beta (also a
-  one-sided significance test).</p>
+analyte concentration that is significantly different from the blank signal
+with a first order error alpha (one-sided significance test).  The detection
+limit, or more precise, the minimum detectable value (German:
+Erfassungsgrenze), is then defined as the signal or analyte concentration
+where the probability that the signal is not detected although the analyte
+is present (type II or false negative error), is beta (also a one-sided
+significance test).</p>
     </div>
 
     <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">lod</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span>, alpha <span class="op">=</span> <span class="fl">0.05</span>, beta <span class="op">=</span> <span class="fl">0.05</span>, method <span class="op">=</span> <span class="st">"default"</span>, tol <span class="op">=</span> <span class="st">"default"</span><span class="op">)</span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">lod</span><span class="op">(</span>
+  <span class="va">object</span>,
+  <span class="va">...</span>,
+  alpha <span class="op">=</span> <span class="fl">0.05</span>,
+  beta <span class="op">=</span> <span class="fl">0.05</span>,
+  method <span class="op">=</span> <span class="st">"default"</span>,
+  tol <span class="op">=</span> <span class="st">"default"</span>
+<span class="op">)</span></code></pre></div>
     </div>
 
     <div id="arguments">
     <h2>Arguments</h2>
     <dl><dt>object</dt>
-<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or 
-    <code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> 
-    with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>, 
-    optionally from a weighted regression.</p></dd>
+<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or
+<code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> with model formula <code>y ~ x</code> or <code>y ~ x -
+1</code>, optionally from a weighted regression.</p></dd>
 <dt>...</dt>
-<dd><p>Placeholder for further arguments that might be needed by 
-    future implementations.</p></dd>
+<dd><p>Placeholder for further arguments that might be needed by
+future implementations.</p></dd>
 <dt>alpha</dt>
 <dd><p>The error tolerance for the decision limit (critical value).</p></dd>
 <dt>beta</dt>
 <dd><p>The error tolerance beta for the detection limit.</p></dd>
 <dt>method</dt>
-<dd><p>The “default” method uses a prediction interval at the LOD
-    for the estimation of the LOD, which obviously requires
-    iteration. This is described for example in Massart, p. 432 ff.
-    The “din” method uses the prediction interval at
-    x = 0 as an approximation.</p></dd>
+<dd><p>The “default” method uses a prediction interval at the
+LOD for the estimation of the LOD, which obviously requires iteration. This
+is described for example in Massart, p. 432 ff.  The “din” method
+uses the prediction interval at x = 0 as an approximation.</p></dd>
 <dt>tol</dt>
 <dd><p>When the “default” method is used, the default tolerance
-    for the LOD on the x scale is the value of the smallest non-zero standard
-    divided by 1000. Can be set to a numeric value to override this.</p></dd>
+for the LOD on the x scale is the value of the smallest non-zero standard
+divided by 1000. Can be set to a numeric value to override this.</p></dd>
 </dl></div>
     <div id="value">
     <h2>Value</h2>
-    <p>A list containig the corresponding x and y values of the estimated limit of
-  detection of a model used for calibration.</p>
+    <p>A list containig the corresponding x and y values of the estimated
+limit of detection of a model used for calibration.</p>
     </div>
     <div id="note">
     <h2>Note</h2>
-    <p>- The default values for alpha and beta are the ones recommended by IUPAC.
-  - 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><a href="https://rdrr.io/r/stats/predict.lm.html" class="external-link">predict.lm</a></code>
-    function, which is currently not supported in R.</p>
+    <p>* The default values for alpha and beta are the ones recommended by IUPAC.
+* 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><a href="https://rdrr.io/r/stats/predict.lm.html" class="external-link">predict.lm</a></code>
+function, which is currently not supported in R.</p>
     </div>
     <div id="references">
     <h2>References</h2>
-    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., 
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  Chapter 13.7.8</p>
+    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong,
+S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, Chapter 13.7.8</p>
 <p>J. Inczedy, T. Lengyel, and A.M. Ure (2002) International Union of Pure and
-  Applied Chemistry Compendium of Analytical Nomenclature: Definitive Rules.
-  Web edition.</p>
-<p>Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
-  detection and quantification capabilities (IUPAC Recommendations 1995). 
-  Analytica Chimica Acta 391, 105 - 126.</p>
+Applied Chemistry Compendium of Analytical Nomenclature: Definitive Rules.
+Web edition.</p>
+<p>Currie, L. A. (1997) Nomenclature in evaluation of analytical methods
+including detection and quantification capabilities (IUPAC Recommendations
+1995).  Analytica Chimica Acta 391, 105 - 126.</p>
     </div>
     <div id="see-also">
     <h2>See also</h2>
@@ -132,7 +137,8 @@
 
     <div id="ref-examples">
     <h2>Examples</h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">din32645</span><span class="op">)</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span>
+<span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">din32645</span><span class="op">)</span></span>
 <span class="r-in"><span class="fu">lod</span><span class="op">(</span><span class="va">m</span><span class="op">)</span> </span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $x</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 0.08655484</span>
@@ -150,6 +156,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> $y</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 3155.393</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"></span>
 </code></pre></div>
     </div>
   </div>
diff --git a/docs/reference/loq.html b/docs/reference/loq.html
index 0960251..86c8f43 100644
--- a/docs/reference/loq.html
+++ b/docs/reference/loq.html
@@ -1,11 +1,10 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Estimate a limit of quantification (LOQ) — loq • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Estimate a limit of quantification (LOQ) — loq"><meta property="og:description" content="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
-    $$L = k c(L)$$
-  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
-  inverse.predict, and L is obtained by iteration."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Estimate a limit of quantification (LOQ) — loq • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Estimate a limit of quantification (LOQ) — loq"><meta property="og:description" content="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 $$L = k c(L)$$
+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
+inverse.predict, and L is obtained by iteration."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--></head><body data-spy="scroll" data-target="#toc">
@@ -53,69 +52,75 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Estimate a limit of quantification (LOQ)</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/loq.R" class="external-link"><code>R/loq.R</code></a></small>
     <div class="hidden name"><code>loq.Rd</code></div>
     </div>
 
     <div class="ref-description">
-    <p>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
-    $$L = k c(L)$$
-  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><a href="inverse.predict.html">inverse.predict</a></code>, and L is obtained by iteration.</p>
+    <p>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 $$L = k c(L)$$
+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><a href="inverse.predict.html">inverse.predict</a></code>, and L is obtained by iteration.</p>
     </div>
 
     <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">loq</span><span class="op">(</span><span class="va">object</span>, <span class="va">...</span>, alpha <span class="op">=</span> <span class="fl">0.05</span>, k <span class="op">=</span> <span class="fl">3</span>, n <span class="op">=</span> <span class="fl">1</span>, w.loq <span class="op">=</span> <span class="st">"auto"</span>,
-    var.loq <span class="op">=</span> <span class="st">"auto"</span>, tol <span class="op">=</span> <span class="st">"default"</span><span class="op">)</span></code></pre></div>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">loq</span><span class="op">(</span>
+  <span class="va">object</span>,
+  <span class="va">...</span>,
+  alpha <span class="op">=</span> <span class="fl">0.05</span>,
+  k <span class="op">=</span> <span class="fl">3</span>,
+  n <span class="op">=</span> <span class="fl">1</span>,
+  w.loq <span class="op">=</span> <span class="st">"auto"</span>,
+  var.loq <span class="op">=</span> <span class="st">"auto"</span>,
+  tol <span class="op">=</span> <span class="st">"default"</span>
+<span class="op">)</span></code></pre></div>
     </div>
 
     <div id="arguments">
     <h2>Arguments</h2>
     <dl><dt>object</dt>
-<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or 
-    <code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> 
-    with model formula <code>y ~ x</code> or <code>y ~ x - 1</code>, 
-    optionally from a weighted regression. If weights are specified
-    in the model, either <code>w.loq</code> or <code>var.loq</code> have to 
-    be specified.</p></dd>
-<dt>alpha</dt>
-<dd><p>The error tolerance for the prediction of x values in the calculation.</p></dd>
+<dd><p>A univariate model object of class <code><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></code> or
+<code><a href="https://rdrr.io/pkg/MASS/man/rlm.html" class="external-link">rlm</a></code> with model formula <code>y ~ x</code> or <code>y ~ x -
+1</code>, optionally from a weighted regression. If weights are specified in the
+model, either <code>w.loq</code> or <code>var.loq</code> have to be specified.</p></dd>
 <dt>...</dt>
-<dd><p>Placeholder for further arguments that might be needed by 
-    future implementations.</p></dd>
+<dd><p>Placeholder for further arguments that might be needed by
+future implementations.</p></dd>
+<dt>alpha</dt>
+<dd><p>The error tolerance for the prediction of x values in the
+calculation.</p></dd>
 <dt>k</dt>
-<dd><p>The inverse of the maximum relative error tolerated at the
-    desired LOQ.</p></dd>
+<dd><p>The inverse of the maximum relative error tolerated at the desired
+LOQ.</p></dd>
 <dt>n</dt>
 <dd><p>The number of replicate measurements for which the LOQ should be
-    specified.</p></dd>
+specified.</p></dd>
 <dt>w.loq</dt>
-<dd><p>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><a href="massart97ex3.html">massart97ex3</a></code> for 
-    an example how to take advantage of knowledge about the 
-    variance function.</p></dd>
+<dd><p>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><a href="massart97ex3.html">massart97ex3</a></code> for an example how to take
+advantage of knowledge about the variance function.</p></dd>
 <dt>var.loq</dt>
-<dd><p>The approximate variance at the LOQ. The default value is 
-    calculated from the model.</p></dd>
+<dd><p>The approximate variance at the LOQ. The default value is
+calculated from the model.</p></dd>
 <dt>tol</dt>
-<dd><p>The default tolerance for the LOQ on the x scale is the value of the
-    smallest non-zero standard divided by 1000. Can be set to a 
-    numeric value to override this.</p></dd>
+<dd><p>The default tolerance for the LOQ on the x scale is the value of
+the smallest non-zero standard divided by 1000. Can be set to a numeric
+value to override this.</p></dd>
 </dl></div>
     <div id="value">
     <h2>Value</h2>
-    <p>The estimated limit of quantification for a model used for calibration.</p>
+    <p>The estimated limit of quantification for a model used for
+calibration.</p>
     </div>
     <div id="note">
     <h2>Note</h2>
-    <p>- 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.</p>
+    <p>* 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.</p>
     </div>
     <div id="see-also">
     <h2>See also</h2>
@@ -124,7 +129,8 @@
 
     <div id="ref-examples">
     <h2>Examples</h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex1</span><span class="op">)</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span>
+<span class="r-in"><span class="va">m</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/stats/lm.html" class="external-link">lm</a></span><span class="op">(</span><span class="va">y</span> <span class="op">~</span> <span class="va">x</span>, data <span class="op">=</span> <span class="va">massart97ex1</span><span class="op">)</span></span>
 <span class="r-in"><span class="fu">loq</span><span class="op">(</span><span class="va">m</span><span class="op">)</span></span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> $x</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 13.97764</span>
@@ -141,6 +147,7 @@
 <span class="r-out co"><span class="r-pr">#&gt;</span> $y</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> [1] 22.68539</span>
 <span class="r-out co"><span class="r-pr">#&gt;</span> </span>
+<span class="r-in"></span>
 </code></pre></div>
     </div>
   </div>
diff --git a/docs/reference/massart97ex1.html b/docs/reference/massart97ex1.html
index e5dd85a..a02dfe0 100644
--- a/docs/reference/massart97ex1.html
+++ b/docs/reference/massart97ex1.html
@@ -47,7 +47,7 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Calibration data from Massart et al. (1997), example 1</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/chemCal-package.R" class="external-link"><code>R/chemCal-package.R</code></a></small>
     <div class="hidden name"><code>massart97ex1.Rd</code></div>
     </div>
 
@@ -55,9 +55,6 @@
     <p>Sample dataset from p. 175 to test the package.</p>
     </div>
 
-    <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu"><a href="https://rdrr.io/r/utils/data.html" class="external-link">data</a></span><span class="op">(</span><span class="va">massart97ex1</span><span class="op">)</span></code></pre></div>
-    </div>
 
     <div id="format">
     <h2>Format</h2>
@@ -65,9 +62,9 @@
     </div>
     <div id="source">
     <h2>Source</h2>
-    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  Chapter 8.</p>
+    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S.,
+Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, Chapter 8.</p>
     </div>
 
   </div>
diff --git a/docs/reference/massart97ex3.html b/docs/reference/massart97ex3.html
index 4196882..5cbdbd6 100644
--- a/docs/reference/massart97ex3.html
+++ b/docs/reference/massart97ex3.html
@@ -47,7 +47,7 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Calibration data from Massart et al. (1997), example 3</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/chemCal-package.R" class="external-link"><code>R/chemCal-package.R</code></a></small>
     <div class="hidden name"><code>massart97ex3.Rd</code></div>
     </div>
 
@@ -55,25 +55,23 @@
     <p>Sample dataset from p. 188 to test the package.</p>
     </div>
 
-    <div id="ref-usage">
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="va">massart97ex3</span></code></pre></div>
-    </div>
 
     <div id="format">
     <h2>Format</h2>
-    <p>A dataframe containing 6 levels of x values with 5
-  observations of y for each level.</p>
+    <p>A dataframe containing 6 levels of x values with 5 observations of y
+for each level.</p>
     </div>
     <div id="source">
     <h2>Source</h2>
-    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  Chapter 8.</p>
+    <p>Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S.,
+Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, Chapter 8.</p>
     </div>
 
     <div id="ref-examples">
     <h2>Examples</h2>
-    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span class="co"># For reproducing the results for replicate standard measurements in example 8,</span></span>
+    <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span>
+<span class="r-in"><span class="co"># For reproducing the results for replicate standard measurements in example 8,</span></span>
 <span class="r-in"><span class="co"># we need to do the calibration on the means when using chemCal &gt; 0.2</span></span>
 <span class="r-in"><span class="va">weights</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/with.html" class="external-link">with</a></span><span class="op">(</span><span class="va">massart97ex3</span>, <span class="op">{</span></span>
 <span class="r-in">  <span class="va">yx</span> <span class="op">&lt;-</span> <span class="fu"><a href="https://rdrr.io/r/base/split.html" class="external-link">split</a></span><span class="op">(</span><span class="va">y</span>, <span class="va">x</span><span class="op">)</span></span>
@@ -149,6 +147,7 @@
 <span class="r-in"><span class="co"># The weight for the loq should therefore be derived at x = 7.3 instead</span></span>
 <span class="r-in"><span class="co"># of 15, but the graphical procedure of Massart (p. 201) to derive the </span></span>
 <span class="r-in"><span class="co"># variances on which the weights are based is quite inaccurate anyway. </span></span>
+<span class="r-in"></span>
 </code></pre></div>
     </div>
   </div>
diff --git a/docs/reference/rl95_cadmium.html b/docs/reference/rl95_cadmium.html
index da9294d..4ddb8e4 100644
--- a/docs/reference/rl95_cadmium.html
+++ b/docs/reference/rl95_cadmium.html
@@ -1,5 +1,7 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato (1995) — rl95_cadmium • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato (1995) — rl95_cadmium"><meta property="og:description" content="Dataset reproduced from Table 1 in Rocke and Lorenzato (1995)."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato
+(1995) — rl95_cadmium • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato
+(1995) — rl95_cadmium"><meta property="og:description" content="Dataset reproduced from Table 1 in Rocke and Lorenzato (1995)."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--></head><body data-spy="scroll" data-target="#toc">
@@ -46,8 +48,9 @@
       </header><div class="row">
   <div class="col-md-9 contents">
     <div class="page-header">
-    <h1>Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato (1995)</h1>
-    
+    <h1>Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato
+(1995)</h1>
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/chemCal-package.R" class="external-link"><code>R/chemCal-package.R</code></a></small>
     <div class="hidden name"><code>rl95_cadmium.Rd</code></div>
     </div>
 
@@ -58,13 +61,13 @@
 
     <div id="format">
     <h2>Format</h2>
-    <p>A dataframe containing four replicate observations for each 
-  of the six calibration standards.</p>
+    <p>A dataframe containing four replicate observations for each of the
+six calibration standards.</p>
     </div>
     <div id="source">
     <h2>Source</h2>
-    <p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
-  measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
+    <p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model
+for measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
     </div>
 
   </div>
diff --git a/docs/reference/rl95_toluene.html b/docs/reference/rl95_toluene.html
index fb071e1..4c8c7d2 100644
--- a/docs/reference/rl95_toluene.html
+++ b/docs/reference/rl95_toluene.html
@@ -1,7 +1,7 @@
 <!DOCTYPE html>
 <!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Toluene amounts measured by GC/MS as reported by Rocke and Lorenzato (1995) — rl95_toluene • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Toluene amounts measured by GC/MS as reported by Rocke and Lorenzato (1995) — rl95_toluene"><meta property="og:description" content="Dataset reproduced from Table 4 in Rocke and Lorenzato (1995). The toluene
-  amount in the calibration samples is given in picograms per 100 µL.
-  Presumably this is the volume that was injected into the instrument."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+amount in the calibration samples is given in picograms per 100 µL.
+Presumably this is the volume that was injected into the instrument."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
 <script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--></head><body data-spy="scroll" data-target="#toc">
@@ -49,26 +49,26 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Toluene amounts measured by GC/MS as reported by Rocke and Lorenzato (1995)</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/chemCal-package.R" class="external-link"><code>R/chemCal-package.R</code></a></small>
     <div class="hidden name"><code>rl95_toluene.Rd</code></div>
     </div>
 
     <div class="ref-description">
     <p>Dataset reproduced from Table 4 in Rocke and Lorenzato (1995). The toluene
-  amount in the calibration samples is given in picograms per 100 µL.
-  Presumably this is the volume that was injected into the instrument.</p>
+amount in the calibration samples is given in picograms per 100 µL.
+Presumably this is the volume that was injected into the instrument.</p>
     </div>
 
 
     <div id="format">
     <h2>Format</h2>
-    <p>A dataframe containing four replicate observations for each
-  of the six calibration standards.</p>
+    <p>A dataframe containing four replicate observations for each of the
+six calibration standards.</p>
     </div>
     <div id="source">
     <h2>Source</h2>
-    <p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
-  measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
+    <p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model
+for measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
     </div>
 
   </div>
diff --git a/docs/reference/utstats14.html b/docs/reference/utstats14.html
index 78d2604..1ffc224 100644
--- a/docs/reference/utstats14.html
+++ b/docs/reference/utstats14.html
@@ -1,6 +1,6 @@
 <!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Example data for calibration with replicates from University of Toronto — utstats14 • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Example data for calibration with replicates from University of Toronto — utstats14"><meta property="og:description" content="Dataset read into R from 
-  https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1.0"><title>Example data for calibration with replicates from University of Toronto — utstats14 • chemCal</title><!-- jquery --><script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script><!-- Bootstrap --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/css/bootstrap.min.css" integrity="sha256-bZLfwXAP04zRMK2BjiO8iu9pf4FbLqX6zitd+tIvLhE=" crossorigin="anonymous"><script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script><!-- bootstrap-toc --><link rel="stylesheet" href="../bootstrap-toc.css"><script src="../bootstrap-toc.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- pkgdown --><link href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Example data for calibration with replicates from University of Toronto — utstats14"><meta property="og:description" content="Dataset read into R from
+https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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 <script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
 <![endif]--></head><body data-spy="scroll" data-target="#toc">
@@ -48,26 +48,27 @@
   <div class="col-md-9 contents">
     <div class="page-header">
     <h1>Example data for calibration with replicates from University of Toronto</h1>
-    
+    <small class="dont-index">Source: <a href="https://github.com/jranke/chemCal/blob/HEAD/R/chemCal-package.R" class="external-link"><code>R/chemCal-package.R</code></a></small>
     <div class="hidden name"><code>utstats14.Rd</code></div>
     </div>
 
     <div class="ref-description">
-    <p>Dataset read into R from 
-  <a href="https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls" class="external-link">https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls</a>.</p>
+    <p>Dataset read into R from
+<a href="https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls" class="external-link">https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls</a>.</p>
     </div>
 
 
     <div id="format">
     <h2>Format</h2>
-    <p>A tibble containing three replicate observations of the response for five
-  calibration concentrations.</p>
+    <p>A tibble containing three replicate observations of the response for
+five calibration concentrations.</p>
     </div>
     <div id="source">
     <h2>Source</h2>
-    <p>David Stone and Jon Ellis (2011) Statistics in Analytical Chemistry. Tutorial website
-  maintained by the Departments of Chemistry, University of Toronto.
-  <a href="https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html" class="external-link">https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html</a></p>
+    <p>David Stone and Jon Ellis (2011) Statistics in Analytical Chemistry.
+Tutorial website maintained by the Departments of Chemistry, University of
+Toronto.
+<a href="https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html" class="external-link">https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html</a></p>
     </div>
 
   </div>
diff --git a/docs/sitemap.xml b/docs/sitemap.xml
index 5d588da..01d9b26 100644
--- a/docs/sitemap.xml
+++ b/docs/sitemap.xml
@@ -19,6 +19,9 @@
     <loc>/news/index.html</loc>
   </url>
   <url>
+    <loc>/reference/calplot.html</loc>
+  </url>
+  <url>
     <loc>/reference/calplot.lm.html</loc>
   </url>
   <url>
diff --git a/man/calplot.Rd b/man/calplot.Rd
new file mode 100644
index 0000000..440d469
--- /dev/null
+++ b/man/calplot.Rd
@@ -0,0 +1,73 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/calplot.R
+\name{calplot}
+\alias{calplot}
+\alias{calplot.default}
+\alias{calplot.lm}
+\title{Plot calibration graphs from univariate linear models}
+\usage{
+calplot(
+  object,
+  xlim = c("auto", "auto"),
+  ylim = c("auto", "auto"),
+  xlab = "Concentration",
+  ylab = "Response",
+  legend_x = "auto",
+  alpha = 0.05,
+  varfunc = NULL
+)
+}
+\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}.}
+
+\item{xlim}{The limits of the plot on the x axis.}
+
+\item{ylim}{The limits of the plot on the y axis.}
+
+\item{xlab}{The label of the x axis.}
+
+\item{ylab}{The label of the y axis.}
+
+\item{legend_x}{An optional numeric value for adjusting the x coordinate of
+the legend.}
+
+\item{alpha}{The error tolerance level for the confidence and prediction
+bands. Note that this includes both tails of the Gaussian distribution,
+unlike the alpha and beta parameters used in \code{\link{lod}} (see note
+below).}
+
+\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. Prediction limits are only shown for
+models from unweighted regression.
+}
+\description{
+Produce graphics of calibration data, the fitted model as well as
+confidence, and, for unweighted regression, prediction bands.
+}
+\note{
+Prediction bands for models from weighted linear regression require
+weights for the data, for which responses should be predicted. Prediction
+intervals using weights e.g. from a variance function are currently not
+supported by the internally used function \code{\link{predict.lm}},
+therefore, \code{calplot} does not draw prediction bands for such models.
+
+It is possible to compare the \code{\link{calplot}} prediction bands with
+the \code{\link{lod}} values if the \code{lod()} alpha and beta parameters
+are half the value of the \code{calplot()} alpha parameter.
+}
+\examples{
+
+data(massart97ex3)
+m <- lm(y ~ x, data = massart97ex3)
+calplot(m)
+
+}
+\author{
+Johannes Ranke
+}
diff --git a/man/calplot.lm.Rd b/man/calplot.lm.Rd
deleted file mode 100644
index 39f20de..0000000
--- a/man/calplot.lm.Rd
+++ /dev/null
@@ -1,72 +0,0 @@
-\name{calplot}
-\alias{calplot}
-\alias{calplot.default}
-\alias{calplot.lm}
-\title{Plot calibration graphs from univariate linear models}
-\description{
-	Produce graphics of calibration data, the fitted model as well
-  as confidence, and, for unweighted regression, prediction bands. 
-}
-\usage{
-  calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"),
-    xlab = "Concentration", ylab = "Response", legend_x = "auto",
-    alpha=0.05, varfunc = NULL)
-}
-\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}.
-  }
-  \item{xlim}{
-    The limits of the plot on the x axis.
-  }
-  \item{ylim}{
-    The limits of the plot on the y axis.
-  }
-  \item{xlab}{
-    The label of the x axis.
-  }
-  \item{ylab}{
-    The label of the y axis.
-  }
-  \item{legend_x}{
-    An optional numeric value for adjusting the x coordinate of the legend.
-  }
-  \item{alpha}{
-    The error tolerance level for the confidence and prediction bands. Note that this 
-    includes both tails of the Gaussian distribution, unlike the alpha and beta parameters
-    used in \code{\link{lod}} (see note below).
-  }
-  \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. Prediction limits are only shown for models from
-  unweighted regression.
-} 
-\note{
-  Prediction bands for models from weighted linear regression require weights
-  for the data, for which responses should be predicted. Prediction intervals
-  using weights e.g. from a variance function are currently not supported by
-  the internally used function \code{\link{predict.lm}}, therefore,
-  \code{calplot} does not draw prediction bands for such models.
-  
-  It is possible to compare the \code{\link{calplot}} prediction bands with the
-  \code{\link{lod}} values if the \code{lod()} alpha and beta parameters are
-  half the value of the \code{calplot()} alpha parameter.
-  
-}
-\examples{
-data(massart97ex3)
-m <- lm(y ~ x, data = massart97ex3)
-calplot(m)
-}
-\author{
-  Johannes Ranke 
-  \email{jranke@uni-bremen.de} 
-}
-\keyword{regression}
diff --git a/man/din32645.Rd b/man/din32645.Rd
index ffcbaed..a8e6a31 100644
--- a/man/din32645.Rd
+++ b/man/din32645.Rd
@@ -1,15 +1,17 @@
-\name{din32645}
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/chemCal-package.R
 \docType{data}
+\name{din32645}
 \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.
+A dataframe containing 10 rows of x and y values.
+}
+\description{
+Sample dataset to test the package.
 }
 \examples{
+
 m <- lm(y ~ x, data = din32645)
 calplot(m)
 
@@ -45,16 +47,17 @@ 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
+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. Formerly available from
-  the Website of the University of Heidelberg.
+Dintest. Plugin for MS Excel for evaluations of calibration data. Written by
+Georg Schmitt, University of Heidelberg. Formerly available from the Website
+of the University of Heidelberg.
 
-  Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
-  detection and quantification capabilities (IUPAC Recommendations 1995). 
-  Analytica Chimica Acta 391, 105 - 126.
+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}
diff --git a/man/inverse.predict.Rd b/man/inverse.predict.Rd
index 373623e..08c24d7 100644
--- a/man/inverse.predict.Rd
+++ b/man/inverse.predict.Rd
@@ -1,67 +1,72 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/inverse.predict.lm.R
 \name{inverse.predict}
 \alias{inverse.predict}
 \alias{inverse.predict.lm}
 \alias{inverse.predict.rlm}
 \alias{inverse.predict.default}
 \title{Predict x from y for a linear calibration}
-\usage{inverse.predict(object, newdata, \dots,
-  ws, alpha=0.05, var.s = "auto")
+\usage{
+inverse.predict(
+  object,
+  newdata,
+  ...,
+  ws = "auto",
+  alpha = 0.05,
+  var.s = "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}.
-  }
-  \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. This argument is obligatory
-    if \code{object} has weights.
-  }
-  \item{alpha}{
-    The error tolerance level for the confidence interval to be reported.
-  }
-  \item{var.s}{
-    The estimated variance of the sample measurements. The default is to take
-    the residual standard error from the calibration and to adjust it
-    using \code{ws}, if applicable. This means that \code{var.s}
-    overrides \code{ws}.
-  }
+\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}.}
+
+\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. This argument is obligatory
+if \code{object} has weights.}
+
+\item{alpha}{The error tolerance level for the confidence interval to be
+reported.}
+
+\item{var.s}{The estimated variance of the sample measurements. The default
+is to take the residual standard error from the calibration and to adjust it
+using \code{ws}, if applicable. This means that \code{var.s} overrides
+\code{ws}.}
 }
 \value{
-  A list containing the predicted x value, its standard error and a
-  confidence interval.
+A list containing the predicted x value, its standard error and a
+confidence interval.
 }
 \description{
-  This function predicts x values using a univariate linear model that has been
-  generated for the purpose of calibrating a measurement method. Prediction
-  intervals are given at the specified confidence level.
-  The calculation method was taken from Massart et al. (1997). In particular,
-  Equations 8.26 and 8.28 were combined in order to yield a general treatment
-  of inverse prediction for univariate linear models, taking into account 
-  weights that have been used to create the linear model, and at the same
-  time providing the possibility to specify a precision in sample measurements
-  differing from the precision in standard samples used for the calibration.
-  This is elaborated in the package vignette.
+This function predicts x values using a univariate linear model that has
+been generated for the purpose of calibrating a measurement method.
+Prediction intervals are given at the specified confidence level.  The
+calculation method was taken from Massart et al. (1997). In particular,
+Equations 8.26 and 8.28 were combined in order to yield a general treatment
+of inverse prediction for univariate linear models, taking into account
+weights that have been used to create the linear model, and at the same time
+providing the possibility to specify a precision in sample measurements
+differing from the precision in standard samples used for the calibration.
+This is elaborated in the package vignette.
+}
+\details{
+This is an implementation of Equation (8.28) in the Handbook of Chemometrics
+and Qualimetrics, Part A, Massart et al (1997), page 200, validated with
+Example 8 on the same page, extended as specified in the package vignette
 }
 \note{
-  The function was validated with examples 7 and 8 from Massart et al. (1997). 
-  Note that the behaviour of inverse.predict changed with chemCal version
-  0.2.1. Confidence intervals for x values obtained from calibrations with
-  replicate measurements did not take the variation about the means into account.
-  Please refer to the vignette for details.}
-\references{
-  Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  p. 200
+The function was validated with examples 7 and 8 from Massart et al.
+(1997).  Note that the behaviour of inverse.predict changed with chemCal
+version 0.2.1. Confidence intervals for x values obtained from calibrations
+with replicate measurements did not take the variation about the means into
+account.  Please refer to the vignette for details.
 }
 \examples{
+
 # This is example 7 from Chapter 8 in Massart et al. (1997)
 m <- lm(y ~ x, data = massart97ex1)
 inverse.predict(m, 15)        #  6.1 +- 4.9
@@ -84,5 +89,10 @@ m3.means <- lm(y ~ x, w = weights, data = massart97ex3.means)
 inverse.predict(m3.means, 15, ws = 1.67)  # 5.9 +- 2.5
 inverse.predict(m3.means, 90, ws = 0.145) # 44.1 +- 7.9
 
+
+}
+\references{
+Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong,
+S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, p. 200
 }
-\keyword{manip}
diff --git a/man/lod.Rd b/man/lod.Rd
index ce32670..05107f3 100644
--- a/man/lod.Rd
+++ b/man/lod.Rd
@@ -1,3 +1,5 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/lod.R
 \name{lod}
 \alias{lod}
 \alias{lod.lm}
@@ -5,83 +7,82 @@
 \alias{lod.default}
 \title{Estimate a limit of detection (LOD)}
 \usage{
-  lod(object, \dots, alpha = 0.05, beta = 0.05, method = "default", tol = "default")
+lod(
+  object,
+  ...,
+  alpha = 0.05,
+  beta = 0.05,
+  method = "default",
+  tol = "default"
+)
 }
 \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.
-  }
-  \item{\dots}{
-    Placeholder for further arguments that might be needed by 
-    future implementations.
-  }
-  \item{alpha}{
-    The error tolerance for the decision limit (critical value).
-  }
-  \item{beta}{
-    The error tolerance beta for the detection limit.
-  }
-  \item{method}{
-    The \dQuote{default} method uses a prediction interval at the LOD
-    for the estimation of the LOD, which obviously requires
-    iteration. This is described for example in Massart, p. 432 ff.
-    The \dQuote{din} method uses the prediction interval at
-    x = 0 as an approximation.
-  }
-  \item{tol}{
-    When the \dQuote{default} method is used, the default tolerance
-    for the LOD on the x scale is the value of the smallest non-zero standard
-    divided by 1000. Can be set to a numeric value to override this.
-  }
+\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.}
+
+\item{\dots}{Placeholder for further arguments that might be needed by
+future implementations.}
+
+\item{alpha}{The error tolerance for the decision limit (critical value).}
+
+\item{beta}{The error tolerance beta for the detection limit.}
+
+\item{method}{The \dQuote{default} method uses a prediction interval at the
+LOD for the estimation of the LOD, which obviously requires iteration. This
+is described for example in Massart, p. 432 ff.  The \dQuote{din} method
+uses the prediction interval at x = 0 as an approximation.}
+
+\item{tol}{When the \dQuote{default} method is used, the default tolerance
+for the LOD on the x scale is the value of the smallest non-zero standard
+divided by 1000. Can be set to a numeric value to override this.}
 }
 \value{
-  A list containig the corresponding x and y values of the estimated limit of
-  detection of a model used for calibration.  
+A list containig the corresponding x and y values of the estimated
+limit of detection of a model used for calibration.
 }
 \description{
-  The decision limit (German: Nachweisgrenze) is defined as the signal or
-  analyte concentration that is significantly different from the blank signal
-  with a first order error alpha (one-sided significance test).
-  The detection limit, or more precise, the minimum detectable value 
-  (German: Erfassungsgrenze), is then defined as the signal or analyte
-  concentration where the probability that the signal is not detected although
-  the analyte is present (type II or false negative error), is beta (also a
-  one-sided significance test).
+The decision limit (German: Nachweisgrenze) is defined as the signal or
+analyte concentration that is significantly different from the blank signal
+with a first order error alpha (one-sided significance test).  The detection
+limit, or more precise, the minimum detectable value (German:
+Erfassungsgrenze), is then defined as the signal or analyte concentration
+where the probability that the signal is not detected although the analyte
+is present (type II or false negative error), is beta (also a one-sided
+significance test).
 }
 \note{
-  - The default values for alpha and beta are the ones recommended by IUPAC.
-  - 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., 
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  Chapter 13.7.8 
-
-  J. Inczedy, T. Lengyel, and A.M. Ure (2002) International Union of Pure and
-  Applied Chemistry Compendium of Analytical Nomenclature: Definitive Rules.
-  Web edition.
-
-  Currie, L. A. (1997) Nomenclature in evaluation of analytical methods including
-  detection and quantification capabilities (IUPAC Recommendations 1995). 
-  Analytica Chimica Acta 391, 105 - 126.
+* The default values for alpha and beta are the ones recommended by IUPAC.
+* 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.
 }
 \examples{
+
 m <- lm(y ~ x, data = din32645)
 lod(m) 
 
 # The critical value (decision limit, German Nachweisgrenze) can be obtained
 # by using beta = 0.5:
 lod(m, alpha = 0.01, beta = 0.5)
+
+}
+\references{
+Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong,
+S., Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, Chapter 13.7.8
+
+J. Inczedy, T. Lengyel, and A.M. Ure (2002) International Union of Pure and
+Applied Chemistry Compendium of Analytical Nomenclature: Definitive Rules.
+Web edition.
+
+Currie, L. A. (1997) Nomenclature in evaluation of analytical methods
+including detection and quantification capabilities (IUPAC Recommendations
+1995).  Analytica Chimica Acta 391, 105 - 126.
 }
 \seealso{
-  Examples for \code{\link{din32645}}  
+Examples for \code{\link{din32645}}
 }
-\keyword{manip}
diff --git a/man/loq.Rd b/man/loq.Rd
index c247f34..390d3a8 100644
--- a/man/loq.Rd
+++ b/man/loq.Rd
@@ -1,3 +1,5 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/loq.R
 \name{loq}
 \alias{loq}
 \alias{loq.lm}
@@ -5,76 +7,74 @@
 \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", tol = "default")
+loq(
+  object,
+  ...,
+  alpha = 0.05,
+  k = 3,
+  n = 1,
+  w.loq = "auto",
+  var.loq = "auto",
+  tol = "default"
+)
 }
 \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.
-  }
-  \item{tol}{
-    The default tolerance for the LOQ on the x scale is the value of the
-    smallest non-zero standard divided by 1000. Can be set to a 
-    numeric value to override this.
-  }
+\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{\dots}{Placeholder for further arguments that might be needed by
+future implementations.}
+
+\item{alpha}{The error tolerance for the prediction of x values in the
+calculation.}
+
+\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.}
+
+\item{tol}{The default tolerance for the LOQ on the x scale is the value of
+the smallest non-zero standard divided by 1000. Can be set to a numeric
+value to override this.}
 }
 \value{
-  The estimated limit of quantification for a model used for calibration.
+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. 
+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.
+* 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{
+
 m <- lm(y ~ x, data = massart97ex1)
 loq(m)
 
 # We can get better by using replicate measurements
 loq(m, n = 3)
+
 }
 \seealso{
-  Examples for \code{\link{din32645}}  
+Examples for \code{\link{din32645}}
 }
-\keyword{manip}
diff --git a/man/massart97ex1.Rd b/man/massart97ex1.Rd
index 44e1b85..d154a9c 100644
--- a/man/massart97ex1.Rd
+++ b/man/massart97ex1.Rd
@@ -1,17 +1,18 @@
-\name{massart97ex1}
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/chemCal-package.R
 \docType{data}
+\name{massart97ex1}
 \alias{massart97ex1}
 \title{Calibration data from Massart et al. (1997), example 1}
-\description{
-  Sample dataset from p. 175 to test the package.
-}
-\usage{data(massart97ex1)}
 \format{
-  A dataframe containing 6 observations of x and y data.
+A dataframe containing 6 observations of x and y data.
 }
 \source{
-  Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  Chapter 8.
+Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S.,
+Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, Chapter 8.
+}
+\description{
+Sample dataset from p. 175 to test the package.
 }
 \keyword{datasets}
diff --git a/man/massart97ex3.Rd b/man/massart97ex3.Rd
index d7f8d00..284a435 100644
--- a/man/massart97ex3.Rd
+++ b/man/massart97ex3.Rd
@@ -1,16 +1,23 @@
-\name{massart97ex3}
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/chemCal-package.R
 \docType{data}
+\name{massart97ex3}
 \alias{massart97ex3}
 \title{Calibration data from Massart et al. (1997), example 3}
-\description{
-  Sample dataset from p. 188 to test the package.
-}
-\usage{massart97ex3}
 \format{
-  A dataframe containing 6 levels of x values with 5
-  observations of y for each level.
+A dataframe containing 6 levels of x values with 5 observations of y
+for each level.
+}
+\source{
+Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S.,
+Lewi, P.J., Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and
+Qualimetrics: Part A, Chapter 8.
+}
+\description{
+Sample dataset from p. 188 to test the package.
 }
 \examples{
+
 # For reproducing the results for replicate standard measurements in example 8,
 # we need to do the calibration on the means when using chemCal > 0.2
 weights <- with(massart97ex3, {
@@ -45,10 +52,6 @@ loq(m3.means, w.loq = 1.67)
 # The weight for the loq should therefore be derived at x = 7.3 instead
 # of 15, but the graphical procedure of Massart (p. 201) to derive the 
 # variances on which the weights are based is quite inaccurate anyway. 
-}
-\source{
-  Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J.,
-  Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A,
-  Chapter 8.
+
 }
 \keyword{datasets}
diff --git a/man/rl95_cadmium.Rd b/man/rl95_cadmium.Rd
index 7ee4222..8e0b02c 100644
--- a/man/rl95_cadmium.Rd
+++ b/man/rl95_cadmium.Rd
@@ -1,16 +1,19 @@
-\name{rl95_cadmium}
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/chemCal-package.R
 \docType{data}
+\name{rl95_cadmium}
 \alias{rl95_cadmium}
-\title{Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato (1995)}
-\description{
-  Dataset reproduced from Table 1 in Rocke and Lorenzato (1995).
-}
+\title{Cadmium concentrations measured by AAS as reported by Rocke and Lorenzato
+(1995)}
 \format{
-  A dataframe containing four replicate observations for each 
-  of the six calibration standards.
+A dataframe containing four replicate observations for each of the
+six calibration standards.
 }
 \source{
-  Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
-  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+Rocke, David M. und Lorenzato, Stefan (1995) A two-component model
+for measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+}
+\description{
+Dataset reproduced from Table 1 in Rocke and Lorenzato (1995).
 }
 \keyword{datasets}
diff --git a/man/rl95_toluene.Rd b/man/rl95_toluene.Rd
index 21fea0f..1f8836a 100644
--- a/man/rl95_toluene.Rd
+++ b/man/rl95_toluene.Rd
@@ -1,18 +1,20 @@
-\name{rl95_toluene}
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/chemCal-package.R
 \docType{data}
+\name{rl95_toluene}
 \alias{rl95_toluene}
 \title{Toluene amounts measured by GC/MS as reported by Rocke and Lorenzato (1995)}
-\description{
-  Dataset reproduced from Table 4 in Rocke and Lorenzato (1995). The toluene
-  amount in the calibration samples is given in picograms per 100 µL.
-  Presumably this is the volume that was injected into the instrument.
-}
 \format{
-  A dataframe containing four replicate observations for each
-  of the six calibration standards.
+A dataframe containing four replicate observations for each of the
+six calibration standards.
 }
 \source{
-  Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
-  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+Rocke, David M. und Lorenzato, Stefan (1995) A two-component model
+for measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+}
+\description{
+Dataset reproduced from Table 4 in Rocke and Lorenzato (1995). The toluene
+amount in the calibration samples is given in picograms per 100 µL.
+Presumably this is the volume that was injected into the instrument.
 }
 \keyword{datasets}
diff --git a/man/utstats14.Rd b/man/utstats14.Rd
index ec41bd5..1b739d4 100644
--- a/man/utstats14.Rd
+++ b/man/utstats14.Rd
@@ -1,18 +1,21 @@
-\name{utstats14}
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/chemCal-package.R
 \docType{data}
+\name{utstats14}
 \alias{utstats14}
 \title{Example data for calibration with replicates from University of Toronto}
-\description{
-  Dataset read into R from 
-  \url{https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls}.
-}
 \format{
-  A tibble containing three replicate observations of the response for five
-  calibration concentrations.
+A tibble containing three replicate observations of the response for
+five calibration concentrations.
 }
 \source{
-  David Stone and Jon Ellis (2011) Statistics in Analytical Chemistry. Tutorial website
-  maintained by the Departments of Chemistry, University of Toronto.
-  \url{https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html}
+David Stone and Jon Ellis (2011) Statistics in Analytical Chemistry.
+Tutorial website maintained by the Departments of Chemistry, University of
+Toronto.
+\url{https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/index.html}
+}
+\description{
+Dataset read into R from
+\url{https://sites.chem.utoronto.ca/chemistry/coursenotes/analsci/stats/files/example14.xls}.
 }
 \keyword{datasets}