From d8d6012e98fb4c7f158bcc7c173407c2b5f3e42e Mon Sep 17 00:00:00 2001 From: ranke Date: Sat, 22 Aug 2015 09:03:10 +0000 Subject: Get rid of the branched svn layout I never used git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@36 5fad18fb-23f0-0310-ab10-e59a3bee62b4 --- man/inverse.predict.Rd | 69 ++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 69 insertions(+) create mode 100644 man/inverse.predict.Rd (limited to 'man/inverse.predict.Rd') diff --git a/man/inverse.predict.Rd b/man/inverse.predict.Rd new file mode 100644 index 0000000..347d670 --- /dev/null +++ b/man/inverse.predict.Rd @@ -0,0 +1,69 @@ +\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") +} +\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}. + } +} +\value{ + 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. +} +\note{ + The function was validated with examples 7 and 8 from Massart et al. (1997). +} +\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 +} +\examples{ +# This is example 7 from Chapter 8 in Massart et al. (1997) +data(massart97ex1) +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 +} +\keyword{manip} -- cgit v1.2.1