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| author | jranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb> | 2013-02-17 23:38:48 +0000 | 
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| committer | jranke <jranke@edb9625f-4e0d-4859-8d74-9fd3b1da38cb> | 2013-02-17 23:38:48 +0000 | 
| commit | 3621ee276c52fd3e5a845f40b43bf0fe8e3416c8 (patch) | |
| tree | d1805eaa498f8487494734e9adac96a26c0469af /vignettes/examples.tex | |
| parent | 86c48be3a34d7d9a43f136719535555d184cbf60 (diff) | |
- Removed vignette files that are built during generation
- Updated the staticdoc documentation
git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@63 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
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| diff --git a/vignettes/examples.tex b/vignettes/examples.tex deleted file mode 100644 index 4f59aa24..00000000 --- a/vignettes/examples.tex +++ /dev/null @@ -1,700 +0,0 @@ -% $Id: examples.Rnw 66 2010-09-03 08:50:26Z jranke $ -%%\VignetteIndexEntry{Examples for kinetic evaluations using mkin} -%%VignetteDepends{FME} -%%\usepackage{Sweave} -\documentclass[12pt,a4paper]{article} -\usepackage{a4wide} -%%\usepackage[lists,heads]{endfloat} -\input{header} -\hypersetup{   -  pdftitle = {Examples for kinetic evaluations using mkin}, -  pdfsubject = {Manuscript}, -  pdfauthor = {Johannes Ranke}, -  colorlinks = {true}, -  linkcolor = {blue}, -  citecolor = {blue}, -  urlcolor = {red}, -  hyperindex = {true}, -  linktocpage = {true}, -} - -\begin{document} -\title{Examples for kinetic evaluations using mkin} -\author{\textbf{Johannes Ranke} \\[0.5cm] -%EndAName -Eurofins Regulatory AG\\ -Weidenweg 15, CH--4310 Rheinfelden, Switzerland\\[0.5cm] -and\\[0.5cm] -University of Bremen\\ -} -\maketitle - -%\begin{abstract} -%\end{abstract} - - -\thispagestyle{empty} \setcounter{page}{0} - -\clearpage - -\tableofcontents - -\textbf{Key words}: Kinetics, FOCUS, nonlinear optimisation - -\section{Kinetic evaluations for parent compounds} -\label{intro} - -These examples are also evaluated in a parallel vignette of the -\Rpackage{kinfit} package \citep{pkg:kinfit}. The datasets are from Appendix 3, -of the FOCUS kinetics report \citep{FOCUS2006, FOCUSkinetics2011}. - -\subsection{Laboratory Data L1} - -The following code defines example dataset L1 from the FOCUS kinetics -report, p. 284 - -\begin{Schunk} -\begin{Sinput} -R> library("mkin") -R> FOCUS_2006_L1 = data.frame( -+   t = rep(c(0, 1, 2, 3, 5, 7, 14, 21, 30), each = 2), -+   parent = c(88.3, 91.4, 85.6, 84.5, 78.9, 77.6,  -+              72.0, 71.9, 50.3, 59.4, 47.0, 45.1, -+              27.7, 27.3, 10.0, 10.4, 2.9, 4.0)) -R> FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1) -\end{Sinput} -\end{Schunk} - -The next step is to set up the models used for the kinetic analysis. Note that -the model definitions contain the names of the observed variables in the data. -In this case, there is only one variable called \Robject{parent}. - -\begin{Schunk} -\begin{Sinput} -R> SFO <- mkinmod(parent = list(type = "SFO")) -R> FOMC <- mkinmod(parent = list(type = "FOMC")) -R> DFOP <- mkinmod(parent = list(type = "DFOP")) -\end{Sinput} -\end{Schunk} - -The three models cover the first assumption of simple first order (SFO), -the case of declining rate constant over time (FOMC) and the case of two -different phases of the kinetics (DFOP). For a more detailed discussion -of the models, please see the FOCUS kinetics report. - -The following two lines fit the model and produce the summary report -of the model fit. This covers the numerical analysis given in the  -FOCUS report. - -\begin{Schunk} -\begin{Sinput} -R> m.L1.SFO <- mkinfit(SFO, FOCUS_2006_L1_mkin, quiet=TRUE) -R> summary(m.L1.SFO) -\end{Sinput} -\begin{Soutput} -mkin version:    0.9.10  -R version:       2.15.2  -Date of fit:     Sat Feb 16 21:38:15 2013  -Date of summary: Sat Feb 16 21:38:15 2013  - -Equations: -[1] d_parent = - k_parent_sink * parent - -Starting values for optimised parameters: -              initial   type transformed -parent_0        100.0  state  100.000000 -k_parent_sink     0.1 deparm   -2.302585 - -Fixed parameter values: -None - -Optimised, transformed parameters: -              Estimate Std. Error -parent_0        92.471      1.368 -k_parent_sink   -2.347      0.041 - -Backtransformed parameters: -              Estimate -parent_0        92.471 -k_parent_sink    0.096 - -Residual standard error: 2.948 on 16 degrees of freedom - -Chi2 error levels in percent: -         err.min n.optim df -All data   3.424       2  7 -parent     3.424       2  7 - -Estimated disappearance times: -        DT50  DT90 -parent 7.249 24.08 - -Estimated formation fractions: -            ff -parent_sink  1 - -Parameter correlation: -              parent_0 k_parent_sink -parent_0        1.0000        0.6248 -k_parent_sink   0.6248        1.0000 - -Data: - time variable observed predicted residual -    0   parent     88.3    92.471  -4.1710 -    0   parent     91.4    92.471  -1.0710 -    1   parent     85.6    84.039   1.5610 -    1   parent     84.5    84.039   0.4610 -    2   parent     78.9    76.376   2.5241 -    2   parent     77.6    76.376   1.2241 -    3   parent     72.0    69.412   2.5884 -    3   parent     71.9    69.412   2.4884 -    5   parent     50.3    57.330  -7.0301 -    5   parent     59.4    57.330   2.0699 -    7   parent     47.0    47.352  -0.3515 -    7   parent     45.1    47.352  -2.2515 -   14   parent     27.7    24.247   3.4527 -   14   parent     27.3    24.247   3.0527 -   21   parent     10.0    12.416  -2.4163 -   21   parent     10.4    12.416  -2.0163 -   30   parent      2.9     5.251  -2.3513 -   30   parent      4.0     5.251  -1.2513 -\end{Soutput} -\end{Schunk} - -A plot of the fit is obtained with the plot function for mkinfit objects. - -\begin{Schunk} -\begin{Sinput} -R> plot(m.L1.SFO) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L1_SFO_plot} - -The residual plot can be obtained using the information contained in the -mkinfit object, which is in fact a derivative of an modFit object defined by -the \Rpackage{FME} package. - -\begin{Schunk} -\begin{Sinput} -R> plot(m.L1.SFO$data$time, m.L1.SFO$data$residual, -+   xlab = "Time", ylab = "Residual", ylim = c(-8, 8)) -R> abline(h = 0, lty = 2) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L1_SFO_residuals} - -For comparison, the FOMC model is fitted as well, and the $\chi^2$ error level -is checked. - -\begin{Schunk} -\begin{Sinput} -R> m.L1.FOMC <- mkinfit(FOMC, FOCUS_2006_L1_mkin, quiet=TRUE) -R> s.m.L1.FOMC <- summary(m.L1.FOMC) -R> s.m.L1.FOMC$errmin -\end{Sinput} -\begin{Soutput} -            err.min n.optim df -All data 0.03618911       3  6 -parent   0.03618911       3  6 -\end{Soutput} -\end{Schunk} - -Due to the higher number of parameters, and the lower number of degrees of freedom -of the fit, the $\chi^2$ error level is actually higher for the FOMC model (3.6\%) than  -for the SFO model (3.4\%). - -\subsection{Laboratory Data L2} - -The following code defines example dataset L2 from the FOCUS kinetics -report, p. 287 - -\begin{Schunk} -\begin{Sinput} -R> library("mkin") -R> FOCUS_2006_L2 = data.frame( -+   t = rep(c(0, 1, 3, 7, 14, 28), each = 2), -+   parent = c(96.1, 91.8, 41.4, 38.7, -+              19.3, 22.3, 4.6, 4.6, -+              2.6, 1.2, 0.3, 0.6)) -R> FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2) -\end{Sinput} -\end{Schunk} - -Again, the SFO model is fitted and a summary is obtained. - -\begin{Schunk} -\begin{Sinput} -R> m.L2.SFO <- mkinfit(SFO, FOCUS_2006_L2_mkin, quiet=TRUE) -R> summary(m.L2.SFO) -\end{Sinput} -\begin{Soutput} -mkin version:    0.9.10  -R version:       2.15.2  -Date of fit:     Sat Feb 16 21:38:15 2013  -Date of summary: Sat Feb 16 21:38:15 2013  - -Equations: -[1] d_parent = - k_parent_sink * parent - -Starting values for optimised parameters: -              initial   type transformed -parent_0        100.0  state  100.000000 -k_parent_sink     0.1 deparm   -2.302585 - -Fixed parameter values: -None - -Optimised, transformed parameters: -              Estimate Std. Error -parent_0       91.4656      3.807 -k_parent_sink  -0.4112      0.107 - -Backtransformed parameters: -              Estimate -parent_0        91.466 -k_parent_sink    0.663 - -Residual standard error: 5.51 on 10 degrees of freedom - -Chi2 error levels in percent: -         err.min n.optim df -All data   14.38       2  4 -parent     14.38       2  4 - -Estimated disappearance times: -        DT50  DT90 -parent 1.046 3.474 - -Estimated formation fractions: -            ff -parent_sink  1 - -Parameter correlation: -              parent_0 k_parent_sink -parent_0        1.0000        0.4295 -k_parent_sink   0.4295        1.0000 - -Data: - time variable observed     predicted residual -    0   parent     96.1 91.4656079103   4.6344 -    0   parent     91.8 91.4656079103   0.3344 -    1   parent     41.4 47.1395280371  -5.7395 -    1   parent     38.7 47.1395280371  -8.4395 -    3   parent     19.3 12.5210295280   6.7790 -    3   parent     22.3 12.5210295280   9.7790 -    7   parent      4.6  0.8833842647   3.7166 -    7   parent      4.6  0.8833842647   3.7166 -   14   parent      2.6  0.0085318162   2.5915 -   14   parent      1.2  0.0085318162   1.1915 -   28   parent      0.3  0.0000007958   0.3000 -   28   parent      0.6  0.0000007958   0.6000 -\end{Soutput} -\end{Schunk} - -The $\chi^2$ error level of 14\% suggests that the model does not fit very well. -This is also obvious from the plots of the fit and the residuals. - -\begin{Schunk} -\begin{Sinput} -R> plot(m.L2.SFO) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L2_SFO_plot} - -In the FOCUS kinetics report, it is stated that there is no apparent systematic -error observed from the residual plot up to the measured DT90 (approximately at -day 5), and there is an underestimation beyond that point. - -\begin{Schunk} -\begin{Sinput} -R> plot(m.L2.SFO$data$time, m.L2.SFO$data$residual, -+   xlab = "Time", ylab = "Residual", ylim = c(-10, 10)) -R> abline(h = 0, lty = 2) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L2_SFO_residuals} - -We may add that it is difficult to judge the random nature of the residuals just  -from the three samplings at days 0, 1 and 3. Also, it is not clear why a -consistent underestimation after the approximate DT90 should be irrelevant. - -For comparison, the FOMC model is fitted as well, and the $\chi^2$ error level -is checked. - -\begin{Schunk} -\begin{Sinput} -R> m.L2.FOMC <- mkinfit(FOMC, FOCUS_2006_L2_mkin, quiet=TRUE) -R> plot(m.L2.FOMC) -R> s.m.L2.FOMC <- summary(m.L2.FOMC) -R> s.m.L2.FOMC$errmin -\end{Sinput} -\begin{Soutput} -            err.min n.optim df -All data 0.06204245       3  3 -parent   0.06204245       3  3 -\end{Soutput} -\end{Schunk} -\includegraphics{examples-L2_FOMC} - -The error level at which the $\chi^2$ test passes is much lower in this case. -Therefore, the FOMC model provides a better description of the data, as less -experimental error has to be assumed in order to explain the data. - -Fitting the four parameter DFOP model does not further reduce the  -$\chi^2$ error level.  - -\begin{Schunk} -\begin{Sinput} -R> m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin, quiet=TRUE) -R> plot(m.L2.DFOP) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L2_DFOP} - -Here, the default starting parameters for the DFOP model obviously do not lead -to a reasonable solution. Therefore the fit is repeated with different starting -parameters. - -\begin{Schunk} -\begin{Sinput} -R> m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin,  -+   parms.ini = c(k1 = 1, k2 = 0.01, g = 0.8), -+   quiet=TRUE) -R> plot(m.L2.DFOP) -R> summary(m.L2.DFOP) -\end{Sinput} -\begin{Soutput} -mkin version:    0.9.10  -R version:       2.15.2  -Date of fit:     Sat Feb 16 21:38:16 2013  -Date of summary: Sat Feb 16 21:38:16 2013  - -Equations: -[1] d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) * parent - -Starting values for optimised parameters: -         initial   type transformed -parent_0   1e+02  state 100.0000000 -k1         1e+00 deparm   0.0000000 -k2         1e-02 deparm  -4.6051702 -g          8e-01 deparm   0.9802581 - -Fixed parameter values: -None - -Optimised, transformed parameters: -         Estimate Std. Error -parent_0  93.9500         NA -k1         4.9589         NA -k2        -1.0880         NA -g         -0.2821         NA - -Backtransformed parameters: -         Estimate -parent_0   93.950 -k1        142.434 -k2          0.337 -g           0.402 - -Residual standard error: 1.732 on 8 degrees of freedom - -Chi2 error levels in percent: -         err.min n.optim df -All data   2.529       4  2 -parent     2.529       4  2 - -Estimated disappearance times: -       DT50 DT90 -parent   NA   NA - -Estimated formation fractions: -[1] ff -<0 rows> (or 0-length row.names) - -Data: - time variable observed predicted residual -    0   parent     96.1 93.950000   2.1500 -    0   parent     91.8 93.950000  -2.1500 -    1   parent     41.4 40.143423   1.2566 -    1   parent     38.7 40.143423  -1.4434 -    3   parent     19.3 20.464500  -1.1645 -    3   parent     22.3 20.464500   1.8355 -    7   parent      4.6  5.318322  -0.7183 -    7   parent      4.6  5.318322  -0.7183 -   14   parent      2.6  0.503070   2.0969 -   14   parent      1.2  0.503070   0.6969 -   28   parent      0.3  0.004501   0.2955 -   28   parent      0.6  0.004501   0.5955 -\end{Soutput} -\begin{Sinput} -R> s.m.L2.DFOP <- summary(m.L2.DFOP) -R> s.m.L2.DFOP$errmin -\end{Sinput} -\begin{Soutput} -            err.min n.optim df -All data 0.02528763       4  2 -parent   0.02528763       4  2 -\end{Soutput} -\end{Schunk} -\includegraphics{examples-L2_DFOP_2} - -Therefore, the FOMC model is clearly the best-fit model based on the  -$\chi^2$ error level criterion. - -\subsection{Laboratory Data L3} - -The following code defines example dataset L3 from the FOCUS kinetics -report, p. 290 - -\begin{Schunk} -\begin{Sinput} -R> library("mkin") -R> FOCUS_2006_L3 = data.frame( -+   t = c(0, 3, 7, 14, 30, 60, 91, 120), -+   parent = c(97.8, 60, 51, 43, 35, 22, 15, 12)) -R> FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3) -\end{Sinput} -\end{Schunk} - -SFO model, summary and plot: - -\begin{Schunk} -\begin{Sinput} -R> m.L3.SFO <- mkinfit(SFO, FOCUS_2006_L3_mkin, quiet=TRUE) -R> summary(m.L3.SFO) -\end{Sinput} -\begin{Soutput} -mkin version:    0.9.10  -R version:       2.15.2  -Date of fit:     Sat Feb 16 21:38:16 2013  -Date of summary: Sat Feb 16 21:38:16 2013  - -Equations: -[1] d_parent = - k_parent_sink * parent - -Starting values for optimised parameters: -              initial   type transformed -parent_0        100.0  state  100.000000 -k_parent_sink     0.1 deparm   -2.302585 - -Fixed parameter values: -None - -Optimised, transformed parameters: -              Estimate Std. Error -parent_0        74.873      8.458 -k_parent_sink   -3.678      0.326 - -Backtransformed parameters: -              Estimate -parent_0        74.873 -k_parent_sink    0.025 - -Residual standard error: 12.91 on 6 degrees of freedom - -Chi2 error levels in percent: -         err.min n.optim df -All data   21.24       2  6 -parent     21.24       2  6 - -Estimated disappearance times: -        DT50  DT90 -parent 27.43 91.12 - -Estimated formation fractions: -            ff -parent_sink  1 - -Parameter correlation: -              parent_0 k_parent_sink -parent_0        1.0000        0.5484 -k_parent_sink   0.5484        1.0000 - -Data: - time variable observed predicted  residual -    0   parent     97.8    74.873  22.92734 -    3   parent     60.0    69.407  -9.40654 -    7   parent     51.0    62.734 -11.73403 -   14   parent     43.0    52.563  -9.56336 -   30   parent     35.0    35.083  -0.08281 -   60   parent     22.0    16.439   5.56137 -   91   parent     15.0     7.510   7.48961 -  120   parent     12.0     3.609   8.39083 -\end{Soutput} -\begin{Sinput} -R> plot(m.L3.SFO) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L3_SFO} - -The $\chi^2$ error level of 22\% as well as the plot suggest that the model -does not fit very well.  - -The FOMC model performs better: - -\begin{Schunk} -\begin{Sinput} -R> m.L3.FOMC <- mkinfit(FOMC, FOCUS_2006_L3_mkin, quiet=TRUE) -R> plot(m.L3.FOMC) -R> s.m.L3.FOMC <- summary(m.L3.FOMC) -R> s.m.L3.FOMC$errmin -\end{Sinput} -\begin{Soutput} -            err.min n.optim df -All data 0.07321867       3  5 -parent   0.07321867       3  5 -\end{Soutput} -\begin{Sinput} -R> endpoints(m.L3.FOMC) -\end{Sinput} -\begin{Soutput} -$distimes -           DT50     DT90 -parent 7.729478 431.2428 - -$ff -logical(0) - -$SFORB -logical(0) -\end{Soutput} -\end{Schunk} -\includegraphics{examples-L3_FOMC} - -The error level at which the $\chi^2$ test passes is 7\% in this case. - -Fitting the four parameter DFOP model further reduces the $\chi^2$ error level -considerably: - -\begin{Schunk} -\begin{Sinput} -R> m.L3.DFOP <- mkinfit(DFOP, FOCUS_2006_L3_mkin, quiet=TRUE) -R> plot(m.L3.DFOP) -R> s.m.L3.DFOP <- summary(m.L3.DFOP) -R> s.m.L3.DFOP$errmin -\end{Sinput} -\begin{Soutput} -            err.min n.optim df -All data 0.02223992       4  4 -parent   0.02223992       4  4 -\end{Soutput} -\end{Schunk} -\includegraphics{examples-L3_DFOP} - -Therefore, the DFOP model is the best-fit model based on the $\chi^2$ error -level criterion for laboratory data L3. - -\subsection{Laboratory Data L4} - -The following code defines example dataset L4 from the FOCUS kinetics -report, p. 293 - -\begin{Schunk} -\begin{Sinput} -R> library("mkin") -R> FOCUS_2006_L4 = data.frame( -+   t = c(0, 3, 7, 14, 30, 60, 91, 120), -+   parent = c(96.6, 96.3, 94.3, 88.8, 74.9, 59.9, 53.5, 49.0)) -R> FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4) -\end{Sinput} -\end{Schunk} - -SFO model, summary and plot: - -\begin{Schunk} -\begin{Sinput} -R> m.L4.SFO <- mkinfit(SFO, FOCUS_2006_L4_mkin, quiet=TRUE) -R> summary(m.L4.SFO) -\end{Sinput} -\begin{Soutput} -mkin version:    0.9.10  -R version:       2.15.2  -Date of fit:     Sat Feb 16 21:38:17 2013  -Date of summary: Sat Feb 16 21:38:17 2013  - -Equations: -[1] d_parent = - k_parent_sink * parent - -Starting values for optimised parameters: -              initial   type transformed -parent_0        100.0  state  100.000000 -k_parent_sink     0.1 deparm   -2.302585 - -Fixed parameter values: -None - -Optimised, transformed parameters: -              Estimate Std. Error -parent_0         96.44      1.949 -k_parent_sink    -5.03      0.080 - -Backtransformed parameters: -              Estimate -parent_0        96.442 -k_parent_sink    0.007 - -Residual standard error: 3.651 on 6 degrees of freedom - -Chi2 error levels in percent: -         err.min n.optim df -All data   3.288       2  6 -parent     3.288       2  6 - -Estimated disappearance times: -       DT50 DT90 -parent  106  352 - -Estimated formation fractions: -            ff -parent_sink  1 - -Parameter correlation: -              parent_0 k_parent_sink -parent_0        1.0000        0.5865 -k_parent_sink   0.5865        1.0000 - -Data: - time variable observed predicted residual -    0   parent     96.6     96.44   0.1585 -    3   parent     96.3     94.57   1.7324 -    7   parent     94.3     92.13   2.1744 -   14   parent     88.8     88.00   0.7972 -   30   parent     74.9     79.26  -4.3589 -   60   parent     59.9     65.14  -5.2376 -   91   parent     53.5     53.18   0.3167 -  120   parent     49.0     43.99   5.0054 -\end{Soutput} -\begin{Sinput} -R> plot(m.L4.SFO) -\end{Sinput} -\end{Schunk} -\includegraphics{examples-L4_SFO} - -The $\chi^2$ error level of 3.3\% as well as the plot suggest that the model -fits very well.  - -The FOMC model for comparison - -\begin{Schunk} -\begin{Sinput} -R> m.L4.FOMC <- mkinfit(FOMC, FOCUS_2006_L4_mkin, quiet=TRUE) -R> plot(m.L4.FOMC) -R> s.m.L4.FOMC <- summary(m.L4.FOMC) -R> s.m.L4.FOMC$errmin -\end{Sinput} -\begin{Soutput} -            err.min n.optim df -All data 0.02027643       3  5 -parent   0.02027643       3  5 -\end{Soutput} -\end{Schunk} -\includegraphics{examples-L4_FOMC} - -The error level at which the $\chi^2$ test passes is slightly lower for the FOMC  -model. However, the difference appears negligible. - -\bibliographystyle{plainnat} -\bibliography{references} - -\end{document} -% vim: set foldmethod=syntax: | 
