Fork the gmkin GUI from mkin. See ChangeLog for details

33 files changed, 0 insertions, 1660 deletions

diff --git a/vignettes/FOCUS_L.Rmd b/vignettes/FOCUS_L.Rmd
deleted file mode 100644
index 957b34a..0000000
--- a/vignettes/FOCUS_L.Rmd
+++ /dev/null
@@ -1,243 +0,0 @@
-<!--

-%\VignetteEngine{knitr::knitr}

-%\VignetteIndexEntry{Example evaluation of FOCUS Laboratory Data L1 to L3}

--->

-

-# Example evaluation of FOCUS Laboratory Data L1 to L3

-

-## Laboratory Data L1

-

-The following code defines example dataset L1 from the FOCUS kinetics

-report, p. 284

-

-```{r}

-library("mkin")

-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))

-FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)

-```

-

-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 `parent`.

-

-```{r}

-SFO <- mkinmod(parent = list(type = "SFO"))

-FOMC <- mkinmod(parent = list(type = "FOMC"))

-DFOP <- mkinmod(parent = list(type = "DFOP"))

-```

-

-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.

-

-```{r}

-m.L1.SFO <- mkinfit(SFO, FOCUS_2006_L1_mkin, quiet=TRUE)

-summary(m.L1.SFO)

-```

-

-A plot of the fit is obtained with the plot function for mkinfit objects.

-

-```{r fig.width=7, fig.height = 5}

-plot(m.L1.SFO)

-```

-The residual plot can be easily obtained by

-

-```{r fig.width=7, fig.height = 5}

-mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")

-```

-

-For comparison, the FOMC model is fitted as well, and the chi^2 error level

-is checked.

-

-```{r}

-m.L1.FOMC <- mkinfit(FOMC, FOCUS_2006_L1_mkin, quiet=TRUE)

-summary(m.L1.FOMC, data = FALSE)

-```

-

-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%). Additionally, the covariance

-matrix can not be obtained, indicating overparameterisation of the model.

-As a consequence, no standard errors for transformed parameters nor

-confidence intervals for backtransformed parameters are available.

-

-The chi^2 error levels reported in Appendix 3 and Appendix 7 to the FOCUS

-kinetics report are rounded to integer percentages and partly deviate by one

-percentage point from the results calculated by mkin. The reason for

-this is not known. However, mkin gives the same chi^2 error levels

-as the kinfit package.

-

-Furthermore, the calculation routines of the kinfit package have been extensively

-compared to the results obtained by the KinGUI software, as documented in the

-kinfit package vignette. KinGUI is a widely used standard package in this field.

-Therefore, the reason for the difference was not investigated further.

-

-## Laboratory Data L2

-

-The following code defines example dataset L2 from the FOCUS kinetics

-report, p. 287

-

-```{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))

-FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)

-```

-

-Again, the SFO model is fitted and a summary is obtained.

-

-```{r}

-m.L2.SFO <- mkinfit(SFO, FOCUS_2006_L2_mkin, quiet=TRUE)

-summary(m.L2.SFO)

-```

-

-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.

-

-```{r fig.height = 8}

-par(mfrow = c(2, 1))

-plot(m.L2.SFO)

-mkinresplot(m.L2.SFO)

-```

-

-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.

-

-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 _a

-priori_ why a consistent underestimation after the approximate DT90 should be

-irrelevant. However, this can be rationalised by the fact that the FOCUS fate

-models generally only implement SFO kinetics.

-

-For comparison, the FOMC model is fitted as well, and the chi^2 error level

-is checked.

-

-```{r fig.height = 8}

-m.L2.FOMC <- mkinfit(FOMC, FOCUS_2006_L2_mkin, quiet = TRUE)

-par(mfrow = c(2, 1))

-plot(m.L2.FOMC)

-mkinresplot(m.L2.FOMC)

-summary(m.L2.FOMC, data = FALSE)

-```

-

-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 further reduces the chi^2 error level. 

-

-```{r fig.height = 5}

-m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin, quiet = TRUE)

-plot(m.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.

-

-```{r fig.height = 5}

-m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin, 

-  parms.ini = c(k1 = 1, k2 = 0.01, g = 0.8),

-  quiet=TRUE)

-plot(m.L2.DFOP)

-summary(m.L2.DFOP, data = FALSE)

-```

-

-Here, the DFOP model is clearly the best-fit model for dataset L2 based on the 

-chi^2 error level criterion. However, the failure to calculate the covariance

-matrix indicates that the parameter estimates correlate excessively. Therefore,

-the FOMC model may be preferred for this dataset.

-

-## Laboratory Data L3

-

-The following code defines example dataset L3 from the FOCUS kinetics report,

-p. 290.

-

-```{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))

-FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)

-```

-

-SFO model, summary and plot:

-

-```{r fig.height = 5}

-m.L3.SFO <- mkinfit(SFO, FOCUS_2006_L3_mkin, quiet = TRUE)

-plot(m.L3.SFO)

-summary(m.L3.SFO)

-```

-

-The chi^2 error level of 21% as well as the plot suggest that the model

-does not fit very well. 

-

-The FOMC model performs better:

-

-```{r fig.height = 5}

-m.L3.FOMC <- mkinfit(FOMC, FOCUS_2006_L3_mkin, quiet = TRUE)

-plot(m.L3.FOMC)

-summary(m.L3.FOMC, data = FALSE)

-```

-

-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:

-

-```{r fig.height = 5}

-m.L3.DFOP <- mkinfit(DFOP, FOCUS_2006_L3_mkin, quiet = TRUE)

-plot(m.L3.DFOP)

-summary(m.L3.DFOP, data = FALSE)

-```

-

-Here, a look to the model plot, the confidence intervals of the parameters 

-and the correlation matrix suggest that the parameter estimates are reliable, and

-the DFOP model can be used as the best-fit model based on the chi^2 error

-level criterion for laboratory data L3.

-

-## Laboratory Data L4

-

-The following code defines example dataset L4 from the FOCUS kinetics

-report, p. 293

-

-```{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))

-FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)

-```

-

-SFO model, summary and plot:

-

-```{r fig.height = 5}

-m.L4.SFO <- mkinfit(SFO, FOCUS_2006_L4_mkin, quiet = TRUE)

-plot(m.L4.SFO)

-summary(m.L4.SFO, data = FALSE)

-```

-

-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

-

-```{r fig.height = 5}

-m.L4.FOMC <- mkinfit(FOMC, FOCUS_2006_L4_mkin, quiet = TRUE)

-plot(m.L4.FOMC)

-summary(m.L4.FOMC, data = FALSE)

-```

-

-The error level at which the chi^2 test passes is slightly lower for the FOMC 

-model. However, the difference appears negligible.

-

diff --git a/vignettes/FOCUS_L.md b/vignettes/FOCUS_L.md
deleted file mode 100644
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--- a/vignettes/FOCUS_L.md
+++ /dev/null
@@ -1,931 +0,0 @@
-<!--
-%\VignetteEngine{knitr::knitr}
-%\VignetteIndexEntry{Example evaluation of FOCUS Laboratory Data L1 to L3}
--->
-
-# Example evaluation of FOCUS Laboratory Data L1 to L3
-
-## Laboratory Data L1
-
-The following code defines example dataset L1 from the FOCUS kinetics
-report, p. 284
-
-
-```r
-library("mkin")
-```
-
-```
-## Loading required package: FME
-## Loading required package: deSolve
-## Loading required package: rootSolve
-## Loading required package: minpack.lm
-## Loading required package: MASS
-## Loading required package: coda
-## Loading required package: lattice
-```
-
-```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, 71.9, 50.3, 59.4, 47, 
-        45.1, 27.7, 27.3, 10, 10.4, 2.9, 4))
-FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)
-```
-
-
-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 `parent`.
-
-
-```r
-SFO <- mkinmod(parent = list(type = "SFO"))
-FOMC <- mkinmod(parent = list(type = "FOMC"))
-DFOP <- mkinmod(parent = list(type = "DFOP"))
-```
-
-
-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.
-
-
-```r
-m.L1.SFO <- mkinfit(SFO, FOCUS_2006_L1_mkin, quiet = TRUE)
-summary(m.L1.SFO)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:54 2013 
-## Date of summary: Sun Nov 17 15:02:54 2013 
-## 
-## Equations:
-## [1] d_parent = - k_parent_sink * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##               value   type transformed
-## parent_0      100.0  state     100.000
-## k_parent_sink   0.1 deparm      -2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##               Estimate Std. Error Lower Upper
-## parent_0         92.50     1.3700 89.60 95.40
-## k_parent_sink    -2.35     0.0406 -2.43 -2.26
-## 
-## Backtransformed parameters:
-##               Estimate   Lower  Upper
-## parent_0       92.5000 89.6000 95.400
-## k_parent_sink   0.0956  0.0877  0.104
-## 
-## Residual standard error: 2.95 on 16 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    3.42       2  7
-## parent      3.42       2  7
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent 7.25 24.1
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##               parent_0 k_parent_sink
-## parent_0         1.000         0.625
-## k_parent_sink    0.625         1.000
-## 
-## Data:
-##  time variable observed predicted residual
-##     0   parent     88.3     92.47   -4.171
-##     0   parent     91.4     92.47   -1.071
-##     1   parent     85.6     84.04    1.561
-##     1   parent     84.5     84.04    0.461
-##     2   parent     78.9     76.38    2.524
-##     2   parent     77.6     76.38    1.224
-##     3   parent     72.0     69.41    2.588
-##     3   parent     71.9     69.41    2.488
-##     5   parent     50.3     57.33   -7.030
-##     5   parent     59.4     57.33    2.070
-##     7   parent     47.0     47.35   -0.352
-##     7   parent     45.1     47.35   -2.252
-##    14   parent     27.7     24.25    3.453
-##    14   parent     27.3     24.25    3.053
-##    21   parent     10.0     12.42   -2.416
-##    21   parent     10.4     12.42   -2.016
-##    30   parent      2.9      5.25   -2.351
-##    30   parent      4.0      5.25   -1.251
-```
-
-
-A plot of the fit is obtained with the plot function for mkinfit objects.
-
-
-```r
-plot(m.L1.SFO)
-```
-
-![plot of chunk unnamed-chunk-4](figure/unnamed-chunk-4.png) 
-
-The residual plot can be easily obtained by
-
-
-```r
-mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
-```
-
-![plot of chunk unnamed-chunk-5](figure/unnamed-chunk-5.png) 
-
-
-For comparison, the FOMC model is fitted as well, and the chi^2 error level
-is checked.
-
-
-```r
-m.L1.FOMC <- mkinfit(FOMC, FOCUS_2006_L1_mkin, quiet = TRUE)
-summary(m.L1.FOMC, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:55 2013 
-## Date of summary: Sun Nov 17 15:02:55 2013 
-## 
-## Equations:
-## [1] d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##          value   type transformed
-## parent_0   100  state     100.000
-## alpha        1 deparm       0.000
-## beta        10 deparm       2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##          Estimate Std. Error Lower Upper
-## parent_0     92.5         NA    NA    NA
-## alpha        25.6         NA    NA    NA
-## beta         28.0         NA    NA    NA
-## 
-## Backtransformed parameters:
-##          Estimate Lower Upper
-## parent_0 9.25e+01    NA    NA
-## alpha    1.35e+11    NA    NA
-## beta     1.41e+12    NA    NA
-## 
-## Residual standard error: 3.05 on 15 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    3.62       3  6
-## parent      3.62       3  6
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent 7.25 24.1
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-## Could not estimate covariance matrix; singular system:
-```
-
-
-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%). Additionally, the covariance
-matrix can not be obtained, indicating overparameterisation of the model.
-As a consequence, no standard errors for transformed parameters nor
-confidence intervals for backtransformed parameters are available.
-
-The chi^2 error levels reported in Appendix 3 and Appendix 7 to the FOCUS
-kinetics report are rounded to integer percentages and partly deviate by one
-percentage point from the results calculated by mkin. The reason for
-this is not known. However, mkin gives the same chi^2 error levels
-as the kinfit package.
-
-Furthermore, the calculation routines of the kinfit package have been extensively
-compared to the results obtained by the KinGUI software, as documented in the
-kinfit package vignette. KinGUI is a widely used standard package in this field.
-Therefore, the reason for the difference was not investigated further.
-
-## Laboratory Data L2
-
-The following code defines example dataset L2 from the FOCUS kinetics
-report, p. 287
-
-
-```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))
-FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)
-```
-
-
-Again, the SFO model is fitted and a summary is obtained.
-
-
-```r
-m.L2.SFO <- mkinfit(SFO, FOCUS_2006_L2_mkin, quiet = TRUE)
-summary(m.L2.SFO)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:55 2013 
-## Date of summary: Sun Nov 17 15:02:55 2013 
-## 
-## Equations:
-## [1] d_parent = - k_parent_sink * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##               value   type transformed
-## parent_0      100.0  state     100.000
-## k_parent_sink   0.1 deparm      -2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##               Estimate Std. Error  Lower  Upper
-## parent_0        91.500      3.810 83.000 99.900
-## k_parent_sink   -0.411      0.107 -0.651 -0.172
-## 
-## Backtransformed parameters:
-##               Estimate  Lower  Upper
-## parent_0        91.500 83.000 99.900
-## k_parent_sink    0.663  0.522  0.842
-## 
-## Residual standard error: 5.51 on 10 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    14.4       2  4
-## parent      14.4       2  4
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent 1.05 3.47
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##               parent_0 k_parent_sink
-## parent_0          1.00          0.43
-## k_parent_sink     0.43          1.00
-## 
-## Data:
-##  time variable observed predicted residual
-##     0   parent     96.1  9.15e+01    4.634
-##     0   parent     91.8  9.15e+01    0.334
-##     1   parent     41.4  4.71e+01   -5.740
-##     1   parent     38.7  4.71e+01   -8.440
-##     3   parent     19.3  1.25e+01    6.779
-##     3   parent     22.3  1.25e+01    9.779
-##     7   parent      4.6  8.83e-01    3.717
-##     7   parent      4.6  8.83e-01    3.717
-##    14   parent      2.6  8.53e-03    2.591
-##    14   parent      1.2  8.53e-03    1.191
-##    28   parent      0.3  7.96e-07    0.300
-##    28   parent      0.6  7.96e-07    0.600
-```
-
-
-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.
-
-
-```r
-par(mfrow = c(2, 1))
-plot(m.L2.SFO)
-mkinresplot(m.L2.SFO)
-```
-
-![plot of chunk unnamed-chunk-9](figure/unnamed-chunk-9.png) 
-
-
-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.
-
-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 _a
-priori_ why a consistent underestimation after the approximate DT90 should be
-irrelevant. However, this can be rationalised by the fact that the FOCUS fate
-models generally only implement SFO kinetics.
-
-For comparison, the FOMC model is fitted as well, and the chi^2 error level
-is checked.
-
-
-```r
-m.L2.FOMC <- mkinfit(FOMC, FOCUS_2006_L2_mkin, quiet = TRUE)
-par(mfrow = c(2, 1))
-plot(m.L2.FOMC)
-mkinresplot(m.L2.FOMC)
-```
-
-![plot of chunk unnamed-chunk-10](figure/unnamed-chunk-10.png) 
-
-```r
-summary(m.L2.FOMC, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:56 2013 
-## Date of summary: Sun Nov 17 15:02:56 2013 
-## 
-## Equations:
-## [1] d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##          value   type transformed
-## parent_0   100  state     100.000
-## alpha        1 deparm       0.000
-## beta        10 deparm       2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##          Estimate Std. Error  Lower  Upper
-## parent_0   93.800      1.860 89.600 98.000
-## alpha       0.318      0.187 -0.104  0.740
-## beta        0.210      0.294 -0.456  0.876
-## 
-## Backtransformed parameters:
-##          Estimate  Lower Upper
-## parent_0    93.80 89.600  98.0
-## alpha        1.37  0.901   2.1
-## beta         1.23  0.634   2.4
-## 
-## Residual standard error: 2.63 on 9 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data     6.2       3  3
-## parent       6.2       3  3
-## 
-## Estimated disappearance times:
-##         DT50 DT90
-## parent 0.809 5.36
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##          parent_0   alpha   beta
-## parent_0   1.0000 -0.0955 -0.186
-## alpha     -0.0955  1.0000  0.976
-## beta      -0.1863  0.9757  1.000
-```
-
-
-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 further reduces the chi^2 error level. 
-
-
-```r
-m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin, quiet = TRUE)
-plot(m.L2.DFOP)
-```
-
-![plot of chunk unnamed-chunk-11](figure/unnamed-chunk-11.png) 
-
-
-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.
-
-
-```r
-m.L2.DFOP <- mkinfit(DFOP, FOCUS_2006_L2_mkin, parms.ini = c(k1 = 1, k2 = 0.01, 
-    g = 0.8), quiet = TRUE)
-plot(m.L2.DFOP)
-```
-
-![plot of chunk unnamed-chunk-12](figure/unnamed-chunk-12.png) 
-
-```r
-summary(m.L2.DFOP, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:57 2013 
-## Date of summary: Sun Nov 17 15:02:57 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
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##          value   type transformed
-## parent_0 1e+02  state    100.0000
-## k1       1e+00 deparm      0.0000
-## k2       1e-02 deparm     -4.6052
-## g        8e-01 deparm      0.9803
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##          Estimate Std. Error Lower Upper
-## parent_0   93.900         NA    NA    NA
-## k1          4.960         NA    NA    NA
-## k2         -1.090         NA    NA    NA
-## g          -0.282         NA    NA    NA
-## 
-## Backtransformed parameters:
-##          Estimate Lower Upper
-## parent_0   93.900    NA    NA
-## k1        142.000    NA    NA
-## k2          0.337    NA    NA
-## g           0.402    NA    NA
-## 
-## Residual standard error: 1.73 on 8 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    2.53       4  2
-## parent      2.53       4  2
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent   NA   NA
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-## Could not estimate covariance matrix; singular system:
-```
-
-
-Here, the DFOP model is clearly the best-fit model for dataset L2 based on the 
-chi^2 error level criterion. However, the failure to calculate the covariance
-matrix indicates that the parameter estimates correlate excessively. Therefore,
-the FOMC model may be preferred for this dataset.
-
-## Laboratory Data L3
-
-The following code defines example dataset L3 from the FOCUS kinetics report,
-p. 290.
-
-
-```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))
-FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)
-```
-
-
-SFO model, summary and plot:
-
-
-```r
-m.L3.SFO <- mkinfit(SFO, FOCUS_2006_L3_mkin, quiet = TRUE)
-plot(m.L3.SFO)
-```
-
-![plot of chunk unnamed-chunk-14](figure/unnamed-chunk-14.png) 
-
-```r
-summary(m.L3.SFO)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:57 2013 
-## Date of summary: Sun Nov 17 15:02:57 2013 
-## 
-## Equations:
-## [1] d_parent = - k_parent_sink * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##               value   type transformed
-## parent_0      100.0  state     100.000
-## k_parent_sink   0.1 deparm      -2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##               Estimate Std. Error Lower Upper
-## parent_0         74.90      8.460 54.20 95.60
-## k_parent_sink    -3.68      0.326 -4.48 -2.88
-## 
-## Backtransformed parameters:
-##               Estimate   Lower   Upper
-## parent_0       74.9000 54.2000 95.6000
-## k_parent_sink   0.0253  0.0114  0.0561
-## 
-## Residual standard error: 12.9 on 6 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    21.2       2  6
-## parent      21.2       2  6
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent 27.4 91.1
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##               parent_0 k_parent_sink
-## parent_0         1.000         0.548
-## k_parent_sink    0.548         1.000
-## 
-## Data:
-##  time variable observed predicted residual
-##     0   parent     97.8     74.87  22.9273
-##     3   parent     60.0     69.41  -9.4065
-##     7   parent     51.0     62.73 -11.7340
-##    14   parent     43.0     52.56  -9.5634
-##    30   parent     35.0     35.08  -0.0828
-##    60   parent     22.0     16.44   5.5614
-##    91   parent     15.0      7.51   7.4896
-##   120   parent     12.0      3.61   8.3908
-```
-
-
-The chi^2 error level of 21% as well as the plot suggest that the model
-does not fit very well. 
-
-The FOMC model performs better:
-
-
-```r
-m.L3.FOMC <- mkinfit(FOMC, FOCUS_2006_L3_mkin, quiet = TRUE)
-plot(m.L3.FOMC)
-```
-
-![plot of chunk unnamed-chunk-15](figure/unnamed-chunk-15.png) 
-
-```r
-summary(m.L3.FOMC, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:57 2013 
-## Date of summary: Sun Nov 17 15:02:57 2013 
-## 
-## Equations:
-## [1] d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##          value   type transformed
-## parent_0   100  state     100.000
-## alpha        1 deparm       0.000
-## beta        10 deparm       2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##          Estimate Std. Error Lower   Upper
-## parent_0   97.000      4.550  85.3 109.000
-## alpha      -0.862      0.170  -1.3  -0.424
-## beta        0.619      0.474  -0.6   1.840
-## 
-## Backtransformed parameters:
-##          Estimate  Lower   Upper
-## parent_0   97.000 85.300 109.000
-## alpha       0.422  0.273   0.655
-## beta        1.860  0.549   6.290
-## 
-## Residual standard error: 4.57 on 5 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    7.32       3  5
-## parent      7.32       3  5
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent 7.73  431
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##          parent_0  alpha   beta
-## parent_0    1.000 -0.151 -0.427
-## alpha      -0.151  1.000  0.911
-## beta       -0.427  0.911  1.000
-```
-
-
-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:
-
-
-```r
-m.L3.DFOP <- mkinfit(DFOP, FOCUS_2006_L3_mkin, quiet = TRUE)
-plot(m.L3.DFOP)
-```
-
-![plot of chunk unnamed-chunk-16](figure/unnamed-chunk-16.png) 
-
-```r
-summary(m.L3.DFOP, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:58 2013 
-## Date of summary: Sun Nov 17 15:02:58 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
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##          value   type transformed
-## parent_0 1e+02  state     100.000
-## k1       1e-01 deparm      -2.303
-## k2       1e-02 deparm      -4.605
-## g        5e-01 deparm       0.000
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##          Estimate Std. Error  Lower    Upper
-## parent_0   97.700     1.4400 93.800 102.0000
-## k1         -0.661     0.1330 -1.030  -0.2910
-## k2         -4.290     0.0590 -4.450  -4.1200
-## g          -0.123     0.0512 -0.265   0.0193
-## 
-## Backtransformed parameters:
-##          Estimate   Lower    Upper
-## parent_0  97.7000 93.8000 102.0000
-## k1         0.5160  0.3560   0.7480
-## k2         0.0138  0.0117   0.0162
-## g          0.4570  0.4070   0.5070
-## 
-## Residual standard error: 1.44 on 4 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    2.23       4  4
-## parent      2.23       4  4
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent 7.46  123
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##          parent_0     k1      k2      g
-## parent_0   1.0000  0.164  0.0131  0.425
-## k1         0.1640  1.000  0.4648 -0.553
-## k2         0.0131  0.465  1.0000 -0.663
-## g          0.4253 -0.553 -0.6631  1.000
-```
-
-
-Here, a look to the model plot, the confidence intervals of the parameters 
-and the correlation matrix suggest that the parameter estimates are reliable, and
-the DFOP model can be used as the best-fit model based on the chi^2 error
-level criterion for laboratory data L3.
-
-## Laboratory Data L4
-
-The following code defines example dataset L4 from the FOCUS kinetics
-report, p. 293
-
-
-```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))
-FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
-```
-
-
-SFO model, summary and plot:
-
-
-```r
-m.L4.SFO <- mkinfit(SFO, FOCUS_2006_L4_mkin, quiet = TRUE)
-plot(m.L4.SFO)
-```
-
-![plot of chunk unnamed-chunk-18](figure/unnamed-chunk-18.png) 
-
-```r
-summary(m.L4.SFO, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:58 2013 
-## Date of summary: Sun Nov 17 15:02:58 2013 
-## 
-## Equations:
-## [1] d_parent = - k_parent_sink * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##               value   type transformed
-## parent_0      100.0  state     100.000
-## k_parent_sink   0.1 deparm      -2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##               Estimate Std. Error Lower  Upper
-## parent_0         96.40       1.95 91.70 101.00
-## k_parent_sink    -5.03       0.08 -5.23  -4.83
-## 
-## Backtransformed parameters:
-##               Estimate    Lower    Upper
-## parent_0      96.40000 91.70000 1.01e+02
-## k_parent_sink  0.00654  0.00538 7.95e-03
-## 
-## Residual standard error: 3.65 on 6 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    3.29       2  6
-## parent      3.29       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         1.000         0.587
-## k_parent_sink    0.587         1.000
-```
-
-
-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
-
-
-```r
-m.L4.FOMC <- mkinfit(FOMC, FOCUS_2006_L4_mkin, quiet = TRUE)
-plot(m.L4.FOMC)
-```
-
-![plot of chunk unnamed-chunk-19](figure/unnamed-chunk-19.png) 
-
-```r
-summary(m.L4.FOMC, data = FALSE)
-```
-
-```
-## mkin version:    0.9.25 
-## R version:       3.0.2 
-## Date of fit:     Sun Nov 17 15:02:59 2013 
-## Date of summary: Sun Nov 17 15:02:59 2013 
-## 
-## Equations:
-## [1] d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent
-## 
-## Method used for solution of differential equation system:
-## analytical 
-## 
-## Weighting: none
-## 
-## Starting values for optimised parameters:
-##          value   type transformed
-## parent_0   100  state     100.000
-## alpha        1 deparm       0.000
-## beta        10 deparm       2.303
-## 
-## Fixed parameter values:
-## None
-## 
-## Optimised, transformed parameters:
-##          Estimate Std. Error Lower   Upper
-## parent_0   99.100      1.680 94.80 103.000
-## alpha      -0.351      0.372 -1.31   0.607
-## beta        4.170      0.564  2.73   5.620
-## 
-## Backtransformed parameters:
-##          Estimate Lower  Upper
-## parent_0   99.100 94.80 103.00
-## alpha       0.704  0.27   1.83
-## beta       65.000 15.30 277.00
-## 
-## Residual standard error: 2.31 on 5 degrees of freedom
-## 
-## Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    2.03       3  5
-## parent      2.03       3  5
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent  109 1644
-## 
-## Estimated formation fractions:
-##             ff
-## parent_sink  1
-## 
-## Parameter correlation:
-##          parent_0  alpha   beta
-## parent_0    1.000 -0.536 -0.608
-## alpha      -0.536  1.000  0.991
-## beta       -0.608  0.991  1.000
-```
-
-
-The error level at which the chi^2 test passes is slightly lower for the FOMC 
-model. However, the difference appears negligible.
-
diff --git a/vignettes/FOCUS_Z.Rnw b/vignettes/FOCUS_Z.Rnw
deleted file mode 100644
index b551007..0000000
--- a/vignettes/FOCUS_Z.Rnw
+++ /dev/null
@@ -1,310 +0,0 @@
-%\VignetteIndexEntry{Examples evaluation of FOCUS dataset Z}
-%\VignetteEngine{knitr::knitr}
-\documentclass[12pt,a4paper]{article}
-\usepackage{a4wide}
-\input{header}
-\hypersetup{  
-  pdftitle = {Example evaluation of FOCUS dataset Z},
-  pdfsubject = {Manuscript},
-  pdfauthor = {Johannes Ranke},
-  colorlinks = {true},
-  linkcolor = {blue},
-  citecolor = {blue},
-  urlcolor = {red},
-  hyperindex = {true},
-  linktocpage = {true},
-}
-
-\begin{document}
-
-<<include=FALSE>>=
-require(knitr)
-opts_chunk$set(engine='R', tidy=FALSE)
-@
-
-\title{Example evaluation of FOCUS dataset Z}
-\author{\textbf{Johannes Ranke} \\[0.5cm]
-%EndAName
-Wissenschaftlicher Berater\\
-Kronacher Str. 8, 79639 Grenzach-Wyhlen, Germany\\[0.5cm]
-and\\[0.5cm]
-University of Bremen\\
-}
-\maketitle
-
-\thispagestyle{empty} \setcounter{page}{0}
-
-\clearpage
-
-\tableofcontents
-
-\textbf{Key words}: Kinetics, FOCUS, nonlinear optimisation
-
-\section{The data}
-
-The following code defines the example dataset from Appendix 7 to the FOCUS kinetics
-report \citep{FOCUSkinetics2011}, p.350.
-
-<<FOCUS_2006_Z_data, echo=TRUE, eval=TRUE>>=
-require(mkin)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21, 
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8, 
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1, 
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5, 
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5, 
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
-
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
-@
-
-\section{Parent compound and one metabolite}
-
-The next step is to set up the models used for the kinetic analysis. As the 
-simultaneous fit of parent and the first metabolite is usually straightforward,
-Step 1 (SFO for parent only) is skipped here. We start with the model 2a, 
-with formation and decline of metabolite Z1 and the pathway from parent
-directly to sink included (default in mkin).
-
-<<FOCUS_2006_Z_fits_1, echo=TRUE, fig.height=4>>=
-Z.2a <- mkinmod(Z0 = list(type = "SFO", to = "Z1"),
-                Z1 = list(type = "SFO"))
-m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot(m.Z.2a)
-summary(m.Z.2a, data = FALSE)
-@
-
-As obvious from the summary, the kinetic rate constant from parent compound Z to sink
-is negligible. Accordingly, the exact magnitude of the fitted parameter 
-\texttt{log k\_Z\_sink} is ill-defined and the covariance matrix is not returned.
-This suggests, in agreement with the analysis in the FOCUS kinetics report, to simplify 
-the model by removing the pathway to sink.
-
-A similar result can be obtained when formation fractions are used in the model 
-formulation:
-
-<<FOCUS_2006_Z_fits_2, echo=TRUE, fig.height=4>>=
-Z.2a.ff <- mkinmod(Z0 = list(type = "SFO", to = "Z1"),
-                   Z1 = list(type = "SFO"),
-                   use_of_ff = "max")
-
-m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot(m.Z.2a.ff)
-summary(m.Z.2a.ff, data = FALSE)
-@
-
-Here, the ilr transformed formation fraction fitted in the model takes a very
-large value, and the backtransformed formation fraction from parent Z to Z1 is
-practically unity. Again, the covariance matrix is not returned as the model is
-overparameterised. 
-
-The simplified model is obtained by setting the list component \texttt{sink} to
-\texttt{FALSE}. 
-
-<<FOCUS_2006_Z_fits_3, echo=TRUE, fig.height=4>>=
-Z.3 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
-               Z1 = list(type = "SFO"))
-m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot(m.Z.3)
-summary(m.Z.3, data = FALSE)
-@
-
-This model definition is not supported when formation fractions 
-are used, but the formation fraction can be fixed to unity.
-
-<<FOCUS_2006_Z_fits_3.ff, echo=TRUE, fig.height=4>>=
-Z.3.ff <- mkinmod(Z0 = list(type = "SFO", to = "Z1"),
-               Z1 = list(type = "SFO"), use_of_ff = "max")
-m.Z.3.ff <- mkinfit(Z.3.ff, FOCUS_2006_Z_mkin, 
-                    parms.ini = c(f_Z0_to_Z1 = 1),
-                    fixed_parms = "f_Z0_to_Z1",
-                    quiet = TRUE)
-summary(m.Z.3.ff, data = FALSE)
-@
-
-\section{Including metabolites Z2 and Z3}
-
-As suggested in the FOCUS report, the pathway to sink was removed for metabolite Z1 as
-well in the next step. While this step appears questionable on the basis of the above results, it 
-is followed here for the purpose of comparison. Also, in the FOCUS report, it is 
-assumed that there is additional empirical evidence that Z1 quickly and exclusively
-hydrolyses to Z2. 
-
-<<FOCUS_2006_Z_fits_5, echo=TRUE, fig.height=4>>=
-Z.5 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
-               Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
-               Z2 = list(type = "SFO"))
-m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot(m.Z.5)
-summary(m.Z.5, data = FALSE)
-@
-
-Finally, metabolite Z3 is added to the model. The fit is accellerated
-by using the starting parameters from the previous fit.
-
-<<FOCUS_2006_Z_fits_6, echo=TRUE, fig.height=4>>=
-Z.FOCUS <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
-                   Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
-                   Z2 = list(type = "SFO", to = "Z3"),
-                   Z3 = list(type = "SFO"))
-m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, 
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
-plot(m.Z.FOCUS)
-summary(m.Z.FOCUS, data = FALSE)
-@
-
-This is the fit corresponding to the final result chosen in Appendix 7 of the 
-FOCUS report. The residual plots can be obtained by
-
-<<FOCUS_2006_Z_residuals_6, echo=TRUE>>=
-par(mfrow = c(2, 2))
-mkinresplot(m.Z.FOCUS, "Z0", lpos = "bottomright")
-mkinresplot(m.Z.FOCUS, "Z1", lpos = "bottomright")
-mkinresplot(m.Z.FOCUS, "Z2", lpos = "bottomright")
-mkinresplot(m.Z.FOCUS, "Z3", lpos = "bottomright")
-@
-
-We can also investigate the confidence interval for the formation
-fraction from Z1 to Z2 by specifying the model using formation
-fractions, and fixing only the formation fraction from Z0 to Z1
-to unity.
-
-<<FOCUS_2006_Z_fits_6_ff, echo=TRUE, fig.height=4>>=
-Z.FOCUS.ff <- mkinmod(Z0 = list(type = "SFO", to = "Z1"),
-                   Z1 = list(type = "SFO", to = "Z2"),
-                   Z2 = list(type = "SFO", to = "Z3"),
-                   Z3 = list(type = "SFO"), use_of_ff = "max")
-m.Z.FOCUS.ff <- mkinfit(Z.FOCUS.ff, FOCUS_2006_Z_mkin,
-                        parms.ini = c(f_Z0_to_Z1 = 1),
-                        fixed_parms = c("f_Z0_to_Z1"), quiet = TRUE) 
-plot(m.Z.FOCUS.ff)
-summary(m.Z.FOCUS.ff, data = FALSE)
-@
-
-\section{Using the SFORB model for parent and metabolites}
-
-As the FOCUS report states, there is a certain tailing of the time course of metabolite 
-Z3. Also, the time course of the parent compound is not fitted very well using the 
-SFO model, as residues at a certain low level remain.
-
-Therefore, an additional model is offered here, using the single first-order 
-reversible binding (SFORB) model for metabolite Z3. As expected, the $\chi^2$
-error level is lower for metabolite Z3 using this model and the graphical 
-fit for Z3 is improved. However, the covariance matrix is not returned.
-
-<<FOCUS_2006_Z_fits_7, echo=TRUE, fig.height=4>>=
-Z.mkin.1 <- mkinmod(Z0 = list(type = "SFO", to = "Z1", sink = FALSE),
-                    Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
-                    Z2 = list(type = "SFO", to = "Z3"),
-                    Z3 = list(type = "SFORB"))
-m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, 
-                      parms.ini = c(k_Z0_Z1 = 0.5, k_Z1_Z2 = 0.3),
-                      quiet = TRUE)
-plot(m.Z.mkin.1)
-summary(m.Z.mkin.1, data = FALSE)
-@
-
-Therefore, a further stepwise model building is performed starting from the
-stage of parent and one metabolite, starting from the assumption that the model
-fit for the parent compound can be improved by using the SFORB model.
-
-<<FOCUS_2006_Z_fits_8, echo=TRUE, fig.height=4>>=
-Z.mkin.2 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
-                    Z1 = list(type = "SFO"))
-m.Z.mkin.2 <- mkinfit(Z.mkin.2, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot(m.Z.mkin.2)
-summary(m.Z.mkin.2, data = FALSE)
-@
-
-When metabolite Z2 is added, the additional sink for Z1 is turned off again,
-for the same reasons as in the original analysis.
-
-<<FOCUS_2006_Z_fits_9, echo=TRUE, fig.height=4>>=
-Z.mkin.3 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
-                    Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
-                    Z2 = list(type = "SFO"))
-m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot(m.Z.mkin.3)
-summary(m.Z.mkin.3, data = FALSE)
-@
-
-This results in a much better representation of the behaviour of the parent 
-compound Z0.
-
-Finally, Z3 is added as well. These models appear overparameterised (no
-covariance matrix returned) if the sink for Z1 is left in the models.
-
-<<FOCUS_2006_Z_fits_10, echo=TRUE, fig.height=4>>=
-Z.mkin.4 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
-                    Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
-                    Z2 = list(type = "SFO", to = "Z3"),
-                    Z3 = list(type = "SFO"))
-m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, 
-                      parms.ini = c(k_Z1_Z2 = 0.05), 
-                      quiet = TRUE)
-plot(m.Z.mkin.4)
-summary(m.Z.mkin.4, data = FALSE)
-@
-
-The error level of the fit, but especially of metabolite Z3, can be improved if
-the SFORB model is chosen for this metabolite, as this model is capable of
-representing the tailing of the metabolite decline phase.
-
-<<FOCUS_2006_Z_fits_11, echo=TRUE, fig.height=4>>=
-Z.mkin.5 <- mkinmod(Z0 = list(type = "SFORB", to = "Z1", sink = FALSE),
-                    Z1 = list(type = "SFO", to = "Z2", sink = FALSE),
-                    Z2 = list(type = "SFO", to = "Z3"),
-                    Z3 = list(type = "SFORB"))
-m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:5],
-                      quiet = TRUE)
-plot(m.Z.mkin.5)
-summary(m.Z.mkin.5, data = FALSE)$bpar
-@
-
-The summary view of the backtransformed parameters shows that we get no
-confidence intervals due to overparameterisation. As the optimized
-\texttt{k\_Z3\_bound\_free} is excessively small, it is reasonable to fix it to
-zero. 
-
-<<FOCUS_2006_Z_fits_11a, echo=TRUE>>=
-m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
-                       parms.ini = c(m.Z.mkin.4$bparms.ode[1:5],
-                                    k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
-summary(m.Z.mkin.5a, data = FALSE)$bpar
-@
-
-A graphical representation of the confidence intervals can finally be obtained.
-<<FOCUS_2006_Z_fits_11b, echo=TRUE>>=
-mkinparplot(m.Z.mkin.5a)
-@
-
-It is clear that nothing can be said about the degradation rate of Z3 towards
-the end of the experiment. However, this appears to be a feature of the data.
-
-<<FOCUS_2006_Z_residuals_11>>=
-par(mfrow = c(2, 2))
-mkinresplot(m.Z.mkin.5, "Z0", lpos = "bottomright")
-mkinresplot(m.Z.mkin.5, "Z1", lpos = "bottomright")
-mkinresplot(m.Z.mkin.5, "Z2", lpos = "bottomright")
-mkinresplot(m.Z.mkin.5, "Z3", lpos = "bottomright")
-@
-
-As expected, the residual plots are much more random than in the case of the 
-all SFO model for which they were shown above. In conclusion, the model
-\texttt{Z.mkin.5} is proposed as the best-fit model for the dataset from
-Appendix 7 of the FOCUS report.
-
-\bibliographystyle{plainnat}
-\bibliography{references}
-
-\end{document}
-% vim: set foldmethod=syntax:
diff --git a/vignettes/FOCUS_Z.pdf b/vignettes/FOCUS_Z.pdf
deleted file mode 100644
index e6138d0..0000000
--- a/vignettes/FOCUS_Z.pdf
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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deleted file mode 100644
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diff --git a/vignettes/header.tex b/vignettes/header.tex
deleted file mode 100644
index 476415e..0000000
--- a/vignettes/header.tex
+++ /dev/null
@@ -1,23 +0,0 @@
-\usepackage{booktabs}

-\usepackage{amsfonts}

-\usepackage{latexsym}

-\usepackage{amsmath}

-\usepackage{amssymb}

-\usepackage{graphicx}

-\usepackage{parskip}

-\usepackage[round]{natbib}

-\usepackage{amstext}

-\usepackage{hyperref}

-\usepackage[utf8]{inputenc}

-

-\newcommand{\Rpackage}[1]{{\normalfont\fontseries{b}\selectfont #1}}

-\newcommand{\Robject}[1]{\texttt{#1}}

-\newcommand{\Rclass}[1]{\textit{#1}}

-\newcommand{\Rcmd}[1]{\texttt{#1}}

-

-\newcommand{\RR}{\textsf{R}}

-

-\RequirePackage[T1]{fontenc}

-\RequirePackage{graphicx,ae,fancyvrb}

-\IfFileExists{upquote.sty}{\RequirePackage{upquote}}{}

-\usepackage{relsize}

diff --git a/vignettes/mkin.Rnw b/vignettes/mkin.Rnw
deleted file mode 100644
index 0ac114e..0000000
--- a/vignettes/mkin.Rnw
+++ /dev/null
@@ -1,74 +0,0 @@
-%\VignetteIndexEntry{Routines for fitting kinetic models with one or more state variables to chemical degradation data}
-%\VignetteEngine{knitr::knitr}
-\documentclass[12pt,a4paper]{article}
-\usepackage{a4wide}
-\input{header}
-\hypersetup{  
-  pdftitle = {mkin - Routines for fitting kinetic models with one or more state variables to chemical degradation data},
-  pdfsubject = {Manuscript},
-  pdfauthor = {Johannes Ranke},
-  colorlinks = {true},
-  linkcolor = {blue},
-  citecolor = {blue},
-  urlcolor = {red},
-  linktocpage = {true},
-}
-
-\begin{document}
-
-<<include=FALSE>>=
-require(knitr)
-opts_chunk$set(engine='R', tidy=FALSE)
-@
-
-\title{mkin -\\
-Routines for fitting kinetic models with one or more state variables to
-chemical degradation data}
-\author{\textbf{Johannes Ranke} \\[0.5cm]
-%EndAName
-Wissenschaftlicher Berater\\
-Kronacher Str. 8, 79639 Grenzach-Wyhlen, Germany\\[0.5cm]
-and\\[0.5cm]
-University of Bremen\\
-}
-\maketitle
-
-\begin{abstract}
-In the regulatory evaluation of chemical substances like plant protection
-products (pesticides), biocides and other chemicals, degradation data play an
-important role. For the evaluation of pesticide degradation experiments, 
-detailed guidance has been developed, based on nonlinear optimisation. 
-The \RR{} add-on package \Rpackage{mkin} implements fitting some of the models
-recommended in this guidance from within R and calculates some statistical
-measures for data series within one or more compartments, for parent and
-metabolites.
-\end{abstract}
-
-
-\thispagestyle{empty} \setcounter{page}{0}
-
-\clearpage
-
-\tableofcontents
-
-\textbf{Key words}: Kinetics, FOCUS, nonlinear optimisation
-
-\section{Introduction}
-\label{intro}
-
-Many approaches are possible regarding the evaluation of chemical degradation
-data.  The \Rpackage{kinfit} package \citep{pkg:kinfit} in \RR{}
-\citep{rcore2013} implements the approach recommended in the kinetics report
-provided by the FOrum for Co-ordination of pesticide fate models and their
-USe \citep{FOCUS2006, FOCUSkinetics2011} for simple data series for one parent
-compound in one compartment.
-
-The \Rpackage{mkin} package \citep{pkg:mkin} extends this approach to data series
-with metabolites and more than one compartment and includes the possibility 
-for back reactions.
-
-\bibliographystyle{plainnat}
-\bibliography{references}
-
-\end{document}
-% vim: set foldmethod=syntax:
diff --git a/vignettes/mkin.pdf b/vignettes/mkin.pdf
deleted file mode 100644
index 42a44d6..0000000
--- a/vignettes/mkin.pdf
+++ /dev/null
diff --git a/vignettes/references.bib b/vignettes/references.bib
deleted file mode 100644
index e069daf..0000000
--- a/vignettes/references.bib
+++ /dev/null
@@ -1,79 +0,0 @@
-% This file was originally created with JabRef 2.7b.
-% Encoding: ISO8859_1
-
-@BOOK{bates88,
-  title = {Nonlinear regression and its applications},
-  publisher = {Wiley-Interscience},
-  year = {1988},
-  author = {D. Bates and D. Watts}
-}
-
-@MANUAL{FOCUSkinetics2011,
-  title = {Generic guidance for estimating persistence and degradation kinetics
-	from environmental fate studies on pesticides in EU registration},
-  author = {{FOCUS Work Group on Degradation Kinetics}},
-  edition = {1.0},
-  month = {November},
-  year = {2011},
-  file = {FOCUS kinetics 2011 Generic guidance:/home/ranke/dok/orgs/focus/FOCUSkineticsvc_1_0_Nov23.pdf:PDF},
-  url = {http://focus.jrc.ec.europa.eu/dk}
-}
-
-@MANUAL{FOCUS2006,
-  title = {Guidance Document on Estimating Persistence and Degradation Kinetics
-	from Environmental Fate Studies on Pesticides in EU Registration.
-	Report of the FOCUS Work Group on Degradation Kinetics},
-  author = {{FOCUS Work Group on Degradation Kinetics}},
-  year = {2006},
-  note = {EC Document Reference Sanco/10058/2005 version 2.0},
-  url = {http://focus.jrc.ec.europa.eu/dk}
-}
-
-@MANUAL{rcore2013,
-  title = {\textsf{R}: A Language and Environment for Statistical Computing},
-  author = {{R Development Core Team}},
-  organization = {R Foundation for Statistical Computing},
-  address = {Vienna, Austria},
-  year = {2013},
-  note = {{ISBN} 3-900051-07-0},
-  url = {http://www.R-project.org}
-}
-
-@MANUAL{pkg:kinfit,
-  title = {kinfit: {R}outines for fitting simple kinetic models to chemical
-	degradation data},
-  author = {Johannes Ranke},
-  year = {2013},
-  url = {http://CRAN.R-project.org/package=kinfit}
-}
-
-@MANUAL{pkg:mkin,
-  title = {mkin: {R}outines for fitting kinetic models with one or more state
-	variables to chemical degradation data},
-  author = {Johannes Ranke},
-  year = {2013},
-  url = {http://CRAN.R-project.org/package/kinfit}
-}
-
-@INPROCEEDINGS{schaefer2007,
-  author = {D. Sch\"{a}fer and M. Mikolasch and P. Rainbird and B. Harvey},
-  title = {{KinGUI}: a new kinetic software tool for evaluations according to
-	FOCUS degradation kinetics},
-  booktitle = {Proceedings of the XIII Symposium Pesticide Chemistry},
-  year = {2007},
-  editor = {Del Re A. A. M. and Capri E. and Fragoulis G. and Trevisan M.},
-  pages = {916--923},
-  address = {Piacenza}
-}
-
-@ARTICLE{soetaert10,
-  author = {Karline Soetaert and Thomas Petzoldt},
-  title = {Inverse Modelling, Sensitivity and Monte Carlo Analysis in {R} Using
-	Package {FME}},
-  journal = {Journal of Statistical Software},
-  year = {2010},
-  volume = {33},
-  pages = {1--28},
-  number = {3},
-  url = {http://www.jstatsoft.org/v33/i03/}
-}