From 6211f3ef4995657798686d8d4ab43ed9406e8a08 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 12 May 2020 16:34:00 +0200 Subject: Update vignettes and docs --- docs/reference/synthetic_data_for_UBA_2014.html | 93 ++++++++++++++----------- 1 file changed, 51 insertions(+), 42 deletions(-) (limited to 'docs/reference/synthetic_data_for_UBA_2014.html') diff --git a/docs/reference/synthetic_data_for_UBA_2014.html b/docs/reference/synthetic_data_for_UBA_2014.html index 6ac7403a..17d2f973 100644 --- a/docs/reference/synthetic_data_for_UBA_2014.html +++ b/docs/reference/synthetic_data_for_UBA_2014.html @@ -10,23 +10,27 @@ - + - + - + + + + + - - + + - + - - + + @@ -52,7 +56,6 @@ Initial concentrations for metabolites and all values where adding the variance As an example, the first dataset has the title SFO_lin_a and is based on the SFO model with two sequential metabolites (linear pathway), with added variance component 'a'. Compare also the code in the example section to see the degradation models." /> - @@ -70,7 +73,7 @@ Compare also the code in the example section to see the degradation models." /> - +
@@ -128,7 +131,12 @@ Compare also the code in the example section to see the degradation models." />
@@ -172,7 +180,7 @@ Compare also the code in the example section to see the degradation models." />

Format

A list containing twelve datasets as an R6 class defined by mkinds, - each containing, among others, the following components

+ each containing, among others, the following components

title

The name of the dataset, e.g. SFO_lin_a

data

A data frame with the data in the form expected by mkinfit

@@ -280,10 +288,10 @@ Compare also the code in the example section to see the degradation models." /> # the generation of the data fit <- mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data, quiet = TRUE) - plot_sep(fit)
summary(fit)
#> mkin version used for fitting: 0.9.49.6 -#> R version used for fitting: 3.6.1 -#> Date of fit: Fri Nov 1 10:10:17 2019 -#> Date of summary: Fri Nov 1 10:10:17 2019 + plot_sep(fit)
summary(fit)
#> mkin version used for fitting: 0.9.50.2 +#> R version used for fitting: 4.0.0 +#> Date of fit: Tue May 12 15:31:29 2020 +#> Date of summary: Tue May 12 15:31:29 2020 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -292,7 +300,7 @@ Compare also the code in the example section to see the degradation models." /> #> #> Model predictions using solution type deSolve #> -#> Fitted using 847 model solutions performed in 2.468 s +#> Fitted using 819 model solutions performed in 0.619 s #> #> Error model: Constant variance #> @@ -321,6 +329,11 @@ Compare also the code in the example section to see the degradation models." /> #> M1_0 0 state #> M2_0 0 state #> +#> Results: +#> +#> AIC BIC logLik +#> 188.7274 200.3723 -87.36368 +#> #> Optimised, transformed parameters with symmetric confidence intervals: #> Estimate Std. Error Lower Upper #> parent_0 102.1000 1.57000 98.8600 105.3000 @@ -339,15 +352,15 @@ Compare also the code in the example section to see the degradation models." /> #> log_k_M2 2.819e-02 7.166e-02 -3.929e-01 1.000e+00 -2.658e-01 #> f_parent_ilr_1 -4.624e-01 -5.682e-01 7.478e-01 -2.658e-01 1.000e+00 #> f_M1_ilr_1 1.614e-01 4.102e-01 -8.109e-01 5.419e-01 -8.605e-01 -#> sigma -3.704e-09 -1.104e-08 5.922e-08 -3.673e-08 5.867e-08 +#> sigma 1.285e-07 1.054e-07 -1.671e-07 3.644e-08 -2.503e-07 #> f_M1_ilr_1 sigma -#> parent_0 1.614e-01 -3.704e-09 -#> log_k_parent 4.102e-01 -1.104e-08 -#> log_k_M1 -8.109e-01 5.922e-08 -#> log_k_M2 5.419e-01 -3.673e-08 -#> f_parent_ilr_1 -8.605e-01 5.867e-08 -#> f_M1_ilr_1 1.000e+00 -8.075e-08 -#> sigma -8.075e-08 1.000e+00 +#> parent_0 1.614e-01 1.285e-07 +#> log_k_parent 4.102e-01 1.054e-07 +#> log_k_M1 -8.109e-01 -1.671e-07 +#> log_k_M2 5.419e-01 3.644e-08 +#> f_parent_ilr_1 -8.605e-01 -2.503e-07 +#> f_M1_ilr_1 1.000e+00 2.636e-07 +#> sigma 2.636e-07 1.000e+00 #> #> Backtransformed parameters: #> Confidence intervals for internally transformed parameters are asymmetric. @@ -384,8 +397,8 @@ Compare also the code in the example section to see the degradation models." /> #> #> Data: #> time variable observed predicted residual -#> 0 parent 101.5 1.021e+02 -0.56248 -#> 0 parent 101.2 1.021e+02 -0.86248 +#> 0 parent 101.5 1.021e+02 -0.56249 +#> 0 parent 101.2 1.021e+02 -0.86249 #> 1 parent 53.9 4.873e+01 5.17118 #> 1 parent 47.5 4.873e+01 -1.22882 #> 3 parent 10.4 1.111e+01 -0.70773 @@ -394,8 +407,8 @@ Compare also the code in the example section to see the degradation models." /> #> 7 parent 0.3 5.772e-01 -0.27717 #> 14 parent 3.5 3.264e-03 3.49674 #> 28 parent 3.2 1.045e-07 3.20000 -#> 90 parent 0.6 -1.875e-11 0.60000 -#> 120 parent 3.5 -2.805e-11 3.50000 +#> 90 parent 0.6 9.531e-10 0.60000 +#> 120 parent 3.5 -5.940e-10 3.50000 #> 1 M1 36.4 3.479e+01 1.61088 #> 1 M1 37.4 3.479e+01 2.61088 #> 3 M1 34.3 3.937e+01 -5.07027 @@ -405,9 +418,9 @@ Compare also the code in the example section to see the degradation models." /> #> 14 M1 5.8 1.995e+00 3.80469 #> 14 M1 1.2 1.995e+00 -0.79531 #> 60 M1 0.5 2.111e-06 0.50000 -#> 90 M1 3.2 2.913e-10 3.20000 -#> 120 M1 1.5 3.625e-11 1.50000 -#> 120 M1 0.6 3.625e-11 0.60000 +#> 90 M1 3.2 -9.670e-10 3.20000 +#> 120 M1 1.5 7.670e-10 1.50000 +#> 120 M1 0.6 7.670e-10 0.60000 #> 1 M2 4.8 4.455e+00 0.34517 #> 3 M2 20.9 2.153e+01 -0.62527 #> 3 M2 19.3 2.153e+01 -2.22527 @@ -425,14 +438,10 @@ Compare also the code in the example section to see the degradation models." /> #> 120 M2 3.3 5.521e+00 -2.22107
# }
- @@ -443,7 +452,7 @@ Compare also the code in the example section to see the degradation models." />
-

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+

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