diff options
| author | ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4> | 2007-10-01 19:44:04 +0000 |
|---|---|---|
| committer | ranke <ranke@5fad18fb-23f0-0310-ab10-e59a3bee62b4> | 2007-10-01 19:44:04 +0000 |
| commit | 14a5af60a36071f6a9b4471fdf183fd91e89e1cd (patch) | |
| tree | 8c845109c3b3e7663b903f3a9d06f7094a4438d8 /inst | |
| parent | 3dec3886b58f73427409d3ef9427c8440420cbc0 (diff) | |
Moved everything into the trunk directory, in order to enable branching
git-svn-id: http://kriemhild.uft.uni-bremen.de/svn/chemCal@22 5fad18fb-23f0-0310-ab10-e59a3bee62b4
Diffstat (limited to 'inst')
| -rw-r--r-- | inst/doc/Makefile | 33 | ||||
| -rw-r--r-- | inst/doc/Rplots.ps | 1970 | ||||
| -rw-r--r-- | inst/doc/chemCal-001.eps | 1762 | ||||
| -rw-r--r-- | inst/doc/chemCal-001.pdf | 1727 | ||||
| -rw-r--r-- | inst/doc/chemCal-002.eps | 288 | ||||
| -rw-r--r-- | inst/doc/chemCal-002.pdf | 275 | ||||
| -rw-r--r-- | inst/doc/chemCal.Rnw | 162 | ||||
| -rw-r--r-- | inst/doc/chemCal.aux | 18 | ||||
| -rw-r--r-- | inst/doc/chemCal.bbl | 0 | ||||
| -rw-r--r-- | inst/doc/chemCal.blg | 46 | ||||
| -rw-r--r-- | inst/doc/chemCal.log | 362 | ||||
| -rw-r--r-- | inst/doc/chemCal.out | 0 | ||||
| -rw-r--r-- | inst/doc/chemCal.pdf | bin | 123694 -> 0 bytes | |||
| -rw-r--r-- | inst/doc/chemCal.tex | 169 |
14 files changed, 0 insertions, 6812 deletions
diff --git a/inst/doc/Makefile b/inst/doc/Makefile deleted file mode 100644 index 8eca69e..0000000 --- a/inst/doc/Makefile +++ /dev/null @@ -1,33 +0,0 @@ -# Makefile for Sweave documents containing both Latex and R code -# Author: Johannes Ranke <jranke@uni-bremen.de> -# Last Change: 2006 Jun 23 -# based on the Makefile of Nicholas Lewin-Koh -# in turn based on work of Rouben Rostmaian -# SVN: $Id: Makefile.rnoweb 62 2006-05-24 08:30:59Z ranke $ - -RNWFILES = $(wildcard *.Rnw) -TARGETS = $(patsubst %.Rnw,%.tex,$(RNWFILE)) $(patsubst %.Rnw,%.pdf,$(RNWFILES)) - -RERUN = "(There were undefined references|Rerun to get (cross-references|the bars) right|Table widths have changed. Rerun LaTeX.|Linenumber reference failed)" -RERUNBIB = "No file.*\.bbl|Citation.*undefined" - -%.tex: %.Rnw - echo 'Sweave("$<")' | R --no-save --no-restore - -%.pdf: %.tex - pdflatex $< - egrep -c $(RERUNBIB) $*.log && (bibtex $*;pdflatex $<); true - egrep $(RERUN) $*.log && (pdflatex $<) ; true - egrep $(RERUN) $*.log && (pdflatex $<) ; true - -all: all-recursive $(TARGETS) - -clean: clean-recursive - rm -f *.aux *.log *.bbl *.blg *.brf *.cb *.ind *.idx *.ilg \ - *.inx *.ps *.dvi *.toc *.out *.lot *~ *.lof *.ttt *.fff - -all-recursive: - for dir in $(wildcard *); do if [ -d $$dir ] && [ -f $$dir/Makefile ]; then cd $$dir; $(MAKE) all; cd ..; fi; done - -clean-recursive: - for dir in $(wildcard *); do if [ -d $$dir ] && [ -f $$dir/Makefile ]; then cd $$dir; $(MAKE) clean; cd ..; fi; done diff --git a/inst/doc/Rplots.ps b/inst/doc/Rplots.ps deleted file mode 100644 index c5e68ec..0000000 --- a/inst/doc/Rplots.ps +++ /dev/null @@ -1,1970 +0,0 @@ -%!PS-Adobe-3.0 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-/Type /Font -/Subtype /Type1 -/Name /F2 -/BaseFont /Helvetica -/Encoding 9 0 R ->> endobj -xref -0 11 -0000000000 65535 f -0000000021 00000 n -0000000163 00000 n -0000005745 00000 n -0000005828 00000 n -0000000212 00000 n -0000000295 00000 n -0000000375 00000 n -0000005725 00000 n -0000005921 00000 n -0000006178 00000 n -trailer -<< -/Size 11 -/Info 1 0 R -/Root 2 0 R ->> -startxref -6275 -%%EOF diff --git a/inst/doc/chemCal.Rnw b/inst/doc/chemCal.Rnw deleted file mode 100644 index 956c664..0000000 --- a/inst/doc/chemCal.Rnw +++ /dev/null @@ -1,162 +0,0 @@ -\documentclass[a4paper]{article} -%\VignetteIndexEntry{Short manual for the chemCal package} -\usepackage{hyperref} - -\title{Basic calibration functions for analytical chemistry} -\author{Johannes Ranke} - -\begin{document} -\maketitle - -The \texttt{chemCal} package was first designed in the course of a lecture and lab -course on "analytics of organic trace contaminants" at the University of Bremen -from October to December 2004. In the fall 2005, an email exchange with -Ron Wehrens led to the belief that it would be desirable to implement the -inverse prediction method given in \cite{massart97} since it also covers the -case of weighted regression. Studies of the IUPAC orange book and of DIN 32645 -as well as publications by Currie and the Analytical Method Committee of the -Royal Society of Chemistry and a nice paper by Castillo and Castells provided -further understanding of the matter. - -At the moment, the package consists of four functions, working on univariate -linear models of class \texttt{lm} or \texttt{rlm}, plus to datasets for -validation. - -A \href{http://bugs.r-project.org/cgi-bin/R/wishlst-fulfilled?id=8877;user=guest}{bug -report (PR\#8877)} and the following e-mail exchange on the r-devel mailing list about -prediction intervals from weighted regression entailed some further studies -on this subject. However, I did not encounter any proof or explanation of the -formula cited below yet, so I can't really confirm that Massart's method is correct. - -When calibrating an analytical method, the first task is to generate a suitable -model. If we want to use the \texttt{chemCal} functions, we will have to -restrict ourselves to univariate, possibly weighted, linear regression so far. - -Once such a model has been created, the calibration can be graphically -shown by using the \texttt{calplot} function: - -<<echo=TRUE,fig=TRUE>>= -library(chemCal) -data(massart97ex3) -m0 <- lm(y ~ x, data = massart97ex3) -calplot(m0) -@ - -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: - -<<echo=TRUE,fig=TRUE>>= -plot(m0,which=3) -@ - -Therefore, in Example 8 in \cite{massart97} weighted regression -is proposed which can be reproduced by - -<<>>= -attach(massart97ex3) -yx <- split(y, x) -ybar <- sapply(yx, mean) -s <- round(sapply(yx, sd), digits = 2) -w <- round(1 / (s^2), digits = 3) -weights <- w[factor(x)] -m <- lm(y ~ x, w = weights) -@ - -If we now want to predict a new x value from measured y values, -we use the \texttt{inverse.predict} function: - -<<>>= -inverse.predict(m, 15, ws=1.67) -inverse.predict(m, 90, ws = 0.145) -@ - -The weight \texttt{ws} assigned to the measured y value has to be -given by the user in the case of weighted regression, or alternatively, -the approximate variance \texttt{var.s} at this location. - -\section*{Theory for \texttt{inverse.predict}} -Equation 8.28 in \cite{massart97} gives a general equation for predicting the -standard error $s_{\hat{x_s}}$ for an x value predicted from measurements of y -according to the linear calibration function $ y = b_0 + b_1 \cdot x$: - -\begin{equation} -s_{\hat{x_s}} = \frac{s_e}{b_1} \sqrt{\frac{1}{w_s m} + \frac{1}{\sum{w_i}} + - \frac{(\bar{y_s} - \bar{y_w})^2 \sum{w_i}} - {{b_1}^2 \left( \sum{w_i} \sum{w_i {x_i}^2} - - {\left( \sum{ w_i x_i } \right)}^2 \right) }} -\end{equation} - -with - -\begin{equation} -s_e = \sqrt{ \frac{\sum w_i (y_i - \hat{y_i})^2}{n - 2}} -\end{equation} - -where $w_i$ is the weight for calibration standard $i$, $y_i$ is the mean $y$ -value (!) observed for standard $i$, $\hat{y_i}$ is the estimated value for -standard $i$, $n$ is the number calibration standards, $w_s$ is the weight -attributed to the sample $s$, $m$ is the number of replicate measurements of -sample $s$, $\bar{y_s}$ is the mean response for the sample, -$\bar{y_w} = \frac{\sum{w_i y_i}}{\sum{w_i}}$ is the weighted mean of responses -$y_i$, and $x_i$ is the given $x$ value for standard $i$. - -The weight $w_s$ for the sample should be estimated or calculated in accordance -to the weights used in the linear regression. - -I adjusted the above equation in order to be able to take a different -precisions in standards and samples into account. In analogy to Equation 8.26 -from \cite{massart97} we get - -\begin{equation} -s_{\hat{x_s}} = \frac{1}{b_1} \sqrt{\frac{{s_s}^2}{w_s m} + - {s_e}^2 \left( \frac{1}{\sum{w_i}} + - \frac{(\bar{y_s} - \bar{y_w})^2 \sum{w_i}} - {{b_1}^2 \left( \sum{w_i} \sum{w_i {x_i}^2} - {\left( \sum{ w_i x_i } \right)}^2 \right) } \right) } -\end{equation} - -where I interpret $\frac{{s_s}^2}{w_s}$ as an estimator of the variance at location -$\hat{x_s}$, which can be replaced by a user-specified value using the argument -\texttt{var.s} of the function \texttt{inverse.predict}. - -\section*{Fitting and using a variance function} - -In the R package \texttt{nlme} variance functions are used for weighted -regressions. But since the \texttt{predict.nlme} method does not calculate -prediction intervals, this is not useful for the \texttt{calplot} function. - -Two approaches could be used for fitting variance functions, one based on -residuals from an unweighted fit, and one based on just the variances -of the different samples along the x axis. If we used the residuals for -fitting, a bias of the model in a certain area would result in a higher -variance, so it seems preferable to choose the second approach. Of course, -a prerequisite is to have sufficient repetitions for each sample in any -case. - -Let's take the above example and estimate a variance function - -<<>>= -massart97ex3 -massart97ex3$x <- factor(massart97ex3$x) -summary <- summaryBy(y~x, data = massart97ex3,FUN=c(mean,sd,var)) -summary$x <- as.numeric(as.vector((summary$x))) -plot(summary$x, summary$y.var, - xlim=c(0,50), - ylim=c(0,max(summary$y.var))) -varModel <- lm(y.var ~ I(x^2) + x, data=summary) -varCurve <- predict(varModel, newdata=data.frame(x=0:5000/100)) -lines(0:5000/100,varCurve) - - - - - -\begin{thebibliography}{1} -\bibitem{massart97} -Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., -Smeyers-Verbeke, J. -\newblock Handbook of Chemometrics and Qualimetrics: Part A, -\newblock Elsevier, Amsterdam, 1997 -\end{thebibliography} - -\end{document} diff --git a/inst/doc/chemCal.aux b/inst/doc/chemCal.aux deleted file mode 100644 index 20bfc98..0000000 --- a/inst/doc/chemCal.aux +++ /dev/null @@ -1,18 +0,0 @@ -\relax -\ifx\hyper@anchor\@undefined -\global \let \oldcontentsline\contentsline -\gdef \contentsline#1#2#3#4{\oldcontentsline{#1}{#2}{#3}} -\global \let \oldnewlabel\newlabel -\gdef \newlabel#1#2{\newlabelxx{#1}#2} -\gdef \newlabelxx#1#2#3#4#5#6{\oldnewlabel{#1}{{#2}{#3}}} -\AtEndDocument{\let \contentsline\oldcontentsline -\let \newlabel\oldnewlabel} -\else -\global \let \hyper@last\relax -\fi - -\citation{massart97} -\citation{massart97} -\citation{massart97} -\citation{massart97} -\bibcite{massart97}{1} diff --git a/inst/doc/chemCal.bbl b/inst/doc/chemCal.bbl deleted file mode 100644 index e69de29..0000000 --- a/inst/doc/chemCal.bbl +++ /dev/null diff --git a/inst/doc/chemCal.blg b/inst/doc/chemCal.blg deleted file mode 100644 index 72f5a0e..0000000 --- a/inst/doc/chemCal.blg +++ /dev/null @@ -1,46 +0,0 @@ -This is BibTeX, Version 0.99c (Web2C 7.5.4) -The top-level auxiliary file: chemCal.aux -I found no \bibdata command---while reading file chemCal.aux -I found no \bibstyle command---while reading file chemCal.aux -You've used 1 entry, - 0 wiz_defined-function locations, - 84 strings with 497 characters, -and the built_in function-call counts, 0 in all, are: -= -- 0 -> -- 0 -< -- 0 -+ -- 0 -- -- 0 -* -- 0 -:= -- 0 -add.period$ -- 0 -call.type$ -- 0 -change.case$ -- 0 -chr.to.int$ -- 0 -cite$ -- 0 -duplicate$ -- 0 -empty$ -- 0 -format.name$ -- 0 -if$ -- 0 -int.to.chr$ -- 0 -int.to.str$ -- 0 -missing$ -- 0 -newline$ -- 0 -num.names$ -- 0 -pop$ -- 0 -preamble$ -- 0 -purify$ -- 0 -quote$ -- 0 -skip$ -- 0 -stack$ -- 0 -substring$ -- 0 -swap$ -- 0 -text.length$ -- 0 -text.prefix$ -- 0 -top$ -- 0 -type$ -- 0 -warning$ -- 0 -while$ -- 0 -width$ -- 0 -write$ -- 0 -(There were 2 error messages) diff --git a/inst/doc/chemCal.log b/inst/doc/chemCal.log deleted file mode 100644 index a21c788..0000000 --- a/inst/doc/chemCal.log +++ /dev/null @@ -1,362 +0,0 @@ -This is pdfeTeX, Version 3.141592-1.21a-2.2 (Web2C 7.5.4) (format=pdflatex 2006.5.30) 23 JUN 2006 18:41 -entering extended mode -**chemCal.tex -(./chemCal.tex -LaTeX2e <2003/12/01> -Babel <v3.8d> and hyphenation patterns for american, french, german, ngerman, b -ahasa, basque, bulgarian, catalan, croatian, czech, danish, dutch, esperanto, e -stonian, finnish, greek, icelandic, irish, italian, latin, magyar, norsk, polis -h, portuges, romanian, russian, serbian, slovak, slovene, spanish, swedish, tur -kish, ukrainian, nohyphenation, loaded. -(/usr/share/texmf-tetex/tex/latex/base/article.cls -Document Class: article 2004/02/16 v1.4f Standard LaTeX document class -(/usr/share/texmf-tetex/tex/latex/base/size10.clo -File: size10.clo 2004/02/16 v1.4f Standard LaTeX file (size option) -) -\c@part=\count79 -\c@section=\count80 -\c@subsection=\count81 -\c@subsubsection=\count82 -\c@paragraph=\count83 -\c@subparagraph=\count84 -\c@figure=\count85 -\c@table=\count86 -\abovecaptionskip=\skip41 -\belowcaptionskip=\skip42 -\bibindent=\dimen102 -) -(/usr/share/texmf-tetex/tex/latex/hyperref/hyperref.sty -Package: hyperref 2003/11/30 v6.74m Hypertext links for LaTeX - 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-\title{Basic calibration functions for analytical chemistry} -\author{Johannes Ranke} - -\usepackage{/usr/share/R/share/texmf/Sweave} -\begin{document} -\maketitle - -The \texttt{chemCal} package was first designed in the course of a lecture and lab -course on "analytics of organic trace contaminants" at the University of Bremen -from October to December 2004. In the fall 2005, an email exchange with -Ron Wehrens led to the belief that it would be desirable to implement the -inverse prediction method given in \cite{massart97} since it also covers the -case of weighted regression. Studies of the IUPAC orange book and of DIN 32645 -as well as publications by Currie and the Analytical Method Committee of the -Royal Society of Chemistry and a nice paper by Castillo and Castells provided -further understanding of the matter. - -At the moment, the package consists of four functions, working on univariate -linear models of class \texttt{lm} or \texttt{rlm}, plus to datasets for -validation. - -A \href{http://bugs.r-project.org/cgi-bin/R/wishlst-fulfilled?id=8877;user=guest}{bug -report (PR\#8877)} and the following e-mail exchange on the r-devel mailing list about -prediction intervals from weighted regression entailed some further studies -on this subject. However, I did not encounter any proof or explanation of the -formula cited below yet, so I can't really confirm that Massart's method is correct. - -When calibrating an analytical method, the first task is to generate a suitable -model. If we want to use the \texttt{chemCal} functions, we will have to restrict -ourselves to univariate, possibly weighted, linear regression so far. - -Once such a model has been created, the calibration can be graphically -shown by using the \texttt{calplot} function: - -\begin{Schunk} -\begin{Sinput} -> library(chemCal) -> data(massart97ex3) -> m0 <- lm(y ~ x, data = massart97ex3) -> calplot(m0) -\end{Sinput} -\end{Schunk} -\includegraphics{chemCal-001} - -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: - -\begin{Schunk} -\begin{Sinput} -> plot(m0, which = 3) -\end{Sinput} -\end{Schunk} -\includegraphics{chemCal-002} - -Therefore, in Example 8 in \cite{massart97} weighted regression -is proposed which can be reproduced by - -\begin{Schunk} -\begin{Sinput} -> attach(massart97ex3) -> yx <- split(y, x) -> ybar <- sapply(yx, mean) -> s <- round(sapply(yx, sd), digits = 2) -> w <- round(1/(s^2), digits = 3) -> weights <- w[factor(x)] -> m <- lm(y ~ x, w = weights) -\end{Sinput} -\end{Schunk} - -If we now want to predict a new x value from measured y values, -we use the \texttt{inverse.predict} function: - -\begin{Schunk} -\begin{Sinput} -> inverse.predict(m, 15, ws = 1.67) -\end{Sinput} -\begin{Soutput} -$Prediction -[1] 5.865367 - -$`Standard Error` -[1] 0.892611 - -$Confidence -[1] 2.478285 - -$`Confidence Limits` -[1] 3.387082 8.343652 -\end{Soutput} -\begin{Sinput} -> inverse.predict(m, 90, ws = 0.145) -\end{Sinput} -\begin{Soutput} -$Prediction -[1] 44.06025 - -$`Standard Error` -[1] 2.829162 - -$Confidence -[1] 7.855012 - -$`Confidence Limits` -[1] 36.20523 51.91526 -\end{Soutput} -\end{Schunk} - -The weight \texttt{ws} assigned to the measured y value has to be -given by the user in the case of weighted regression, or alternatively, -the approximate variance \texttt{var.s} at this location. - -\section*{Theory for \texttt{inverse.predict}} -Equation 8.28 in \cite{massart97} gives a general equation for predicting the -standard error $s_{\hat{x_s}}$ for an x value predicted from measurements of y -according to the linear calibration function $ y = b_0 + b_1 \cdot x$: - -\begin{equation} -s_{\hat{x_s}} = \frac{s_e}{b_1} \sqrt{\frac{1}{w_s m} + \frac{1}{\sum{w_i}} + - \frac{(\bar{y_s} - \bar{y_w})^2 \sum{w_i}} - {{b_1}^2 \left( \sum{w_i} \sum{w_i {x_i}^2} - - {\left( \sum{ w_i x_i } \right)}^2 \right) }} -\end{equation} - -with - -\begin{equation} -s_e = \sqrt{ \frac{\sum w_i (y_i - \hat{y_i})^2}{n - 2}} -\end{equation} - -where $w_i$ is the weight for calibration standard $i$, $y_i$ is the mean $y$ -value (!) observed for standard $i$, $\hat{y_i}$ is the estimated value for -standard $i$, $n$ is the number calibration standards, $w_s$ is the weight -attributed to the sample $s$, $m$ is the number of replicate measurements of -sample $s$, $\bar{y_s}$ is the mean response for the sample, -$\bar{y_w} = \frac{\sum{w_i y_i}}{\sum{w_i}}$ is the weighted mean of responses -$y_i$, and $x_i$ is the given $x$ value for standard $i$. - -The weight $w_s$ for the sample should be estimated or calculated in accordance -to the weights used in the linear regression. - -I adjusted the above equation in order to be able to take a different -precisions in standards and samples into account. In analogy to Equation 8.26 -from \cite{massart97} we get - -\begin{equation} -s_{\hat{x_s}} = \frac{1}{b_1} \sqrt{\frac{{s_s}^2}{w_s m} + - {s_e}^2 \left( \frac{1}{\sum{w_i}} + - \frac{(\bar{y_s} - \bar{y_w})^2 \sum{w_i}} - {{b_1}^2 \left( \sum{w_i} \sum{w_i {x_i}^2} - {\left( \sum{ w_i x_i } \right)}^2 \right) } \right) } -\end{equation} - -where I interpret $\frac{{s_s}^2}{w_s}$ as an estimator of the variance at location -$\hat{x_s}$, which can be replaced by a user-specified value using the argument -\texttt{var.s} of the function \texttt{inverse.predict}. - -\begin{thebibliography}{1} -\bibitem{massart97} -Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., -Smeyers-Verbeke, J. -\newblock Handbook of Chemometrics and Qualimetrics: Part A, -\newblock Elsevier, Amsterdam, 1997 -\end{thebibliography} - -\end{document} |