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diff --git a/man/inverse.predict.Rd b/man/inverse.predict.Rd
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--- 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}

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