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Diffstat (limited to 'vignettes')
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 index 6c43889..0000000 --- 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) -``` - - - -The residual plot can be easily obtained by - - -```r -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) -``` - -``` -## 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) -``` - - - - -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) -``` - - - -```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) -``` - - - - -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) -``` - - - -```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) -``` - - - -```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) -``` - - - -```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) -``` - - - -```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) -``` - - - -```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) -``` - - - -```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 Binary files differdeleted file mode 100644 index e6138d0..0000000 --- a/vignettes/FOCUS_Z.pdf +++ /dev/null diff --git a/vignettes/figure/FOCUS_2006_Z_fits_1.pdf b/vignettes/figure/FOCUS_2006_Z_fits_1.pdf Binary files differdeleted file mode 100644 index 7533073..0000000 --- a/vignettes/figure/FOCUS_2006_Z_fits_1.pdf +++ /dev/null diff --git a/vignettes/figure/FOCUS_2006_Z_fits_10.pdf b/vignettes/figure/FOCUS_2006_Z_fits_10.pdf Binary files differdeleted file mode 100644 index 5ebd381..0000000 --- a/vignettes/figure/FOCUS_2006_Z_fits_10.pdf +++ /dev/null diff --git a/vignettes/figure/FOCUS_2006_Z_fits_11.pdf b/vignettes/figure/FOCUS_2006_Z_fits_11.pdf Binary files differdeleted file mode 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-\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}}
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-\newcommand{\RR}{\textsf{R}}
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-\RequirePackage[T1]{fontenc}
-\RequirePackage{graphicx,ae,fancyvrb}
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-\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 Binary files differdeleted 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/} -} |
