diff options
| -rw-r--r-- | GNUmakefile | 2 | ||||
| -rw-r--r-- | docs/articles/FOCUS_D.html | 8 | ||||
| -rw-r--r-- | docs/articles/FOCUS_L.html | 42 | ||||
| -rw-r--r-- | docs/articles/mkin.html | 2 | ||||
| -rw-r--r-- | docs/articles/twa.html | 2 | ||||
| -rw-r--r-- | docs/articles/web_only/FOCUS_Z.html | 2 | ||||
| -rw-r--r-- | docs/articles/web_only/NAFTA_examples.html | 2 | ||||
| -rw-r--r-- | docs/articles/web_only/benchmarks.html | 24 | ||||
| -rw-r--r-- | docs/articles/web_only/compiled_models.html | 12 | ||||
| -rw-r--r-- | docs/reference/index.html | 2 | ||||
| -rw-r--r-- | docs/reference/mkinfit.html | 28 | ||||
| -rw-r--r-- | docs/reference/mkinmod.html | 2 | ||||
| -rw-r--r-- | docs/reference/mkinpredict.html | 6 | ||||
| -rw-r--r-- | docs/reference/mmkin.html | 4 | ||||
| -rw-r--r-- | docs/reference/summary.mkinfit.html | 6 | ||||
| -rw-r--r-- | docs/reference/synthetic_data_for_UBA_2014-1.png | bin | 0 -> 62975 bytes | |||
| -rw-r--r-- | docs/reference/synthetic_data_for_UBA_2014.html | 462 | ||||
| -rw-r--r-- | docs/sitemap.xml | 2 | ||||
| -rw-r--r-- | man/synthetic_data_for_UBA_2014.Rd | 292 | ||||
| -rw-r--r-- | vignettes/mkin_benchmarks.rda | bin | 880 -> 875 bytes |
20 files changed, 681 insertions, 219 deletions
diff --git a/GNUmakefile b/GNUmakefile index 816cf1fb..0084267a 100644 --- a/GNUmakefile +++ b/GNUmakefile @@ -87,7 +87,7 @@ vignettes/web_only/%.html: vignettes/references.bib vignettes/web_only/%.Rmd articles: vignettes/web_only/FOCUS_Z.html vignettes/web_only/compiled_models.html pd: - "$(RBIN)/Rscript" -e "pkgdown::build_site(run_dont_run = TRUE)" + "$(RBIN)/Rscript" -e "pkgdown::build_site(run_dont_run = TRUE, lazy = TRUE)" git add -A git commit -m 'Static documentation rebuilt by pkgdown' -e diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index 53164ffd..f8c51e2d 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -90,7 +90,7 @@ <h1>Example evaluation of FOCUS Example Dataset D</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>FOCUS_D.Rmd</code></div> @@ -170,8 +170,8 @@ <div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb11-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(fit)</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:07 2019 -## Date of summary: Wed Sep 18 18:24:08 2019 +## Date of fit: Thu Sep 19 09:52:55 2019 +## Date of summary: Thu Sep 19 09:52:56 2019 ## ## Equations: ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent @@ -179,7 +179,7 @@ ## ## Model predictions using solution type deSolve ## -## Fitted using 389 model solutions performed in 1.014 s +## Fitted using 389 model solutions performed in 1.001 s ## ## Error model: Constant variance ## diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html index 50c83db6..7b35beeb 100644 --- a/docs/articles/FOCUS_L.html +++ b/docs/articles/FOCUS_L.html @@ -90,7 +90,7 @@ <h1>Example evaluation of FOCUS Laboratory Data L1 to L3</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>FOCUS_L.Rmd</code></div> @@ -116,8 +116,8 @@ <a class="sourceLine" id="cb2-2" title="2"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(m.L1.SFO)</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:09 2019 -## Date of summary: Wed Sep 18 18:24:09 2019 +## Date of fit: Thu Sep 19 09:52:57 2019 +## Date of summary: Thu Sep 19 09:52:57 2019 ## ## Equations: ## d_parent/dt = - k_parent_sink * parent @@ -218,8 +218,8 @@ ## finite result is doubtful</code></pre> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:12 2019 -## Date of summary: Wed Sep 18 18:24:12 2019 +## Date of fit: Thu Sep 19 09:52:59 2019 +## Date of summary: Thu Sep 19 09:52:59 2019 ## ## ## Warning: Optimisation did not converge: @@ -231,7 +231,7 @@ ## ## Model predictions using solution type analytical ## -## Fitted using 899 model solutions performed in 1.954 s +## Fitted using 899 model solutions performed in 1.908 s ## ## Error model: Constant variance ## @@ -323,15 +323,15 @@ <div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(m.L2.FOMC, <span class="dt">data =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:13 2019 -## Date of summary: Wed Sep 18 18:24:13 2019 +## Date of fit: Thu Sep 19 09:53:00 2019 +## Date of summary: Thu Sep 19 09:53:00 2019 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 239 model solutions performed in 0.497 s +## Fitted using 239 model solutions performed in 0.49 s ## ## Error model: Constant variance ## @@ -399,8 +399,8 @@ <div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb20-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(m.L2.DFOP, <span class="dt">data =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:14 2019 -## Date of summary: Wed Sep 18 18:24:14 2019 +## Date of fit: Thu Sep 19 09:53:02 2019 +## Date of summary: Thu Sep 19 09:53:02 2019 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * @@ -409,7 +409,7 @@ ## ## Model predictions using solution type analytical ## -## Fitted using 572 model solutions performed in 1.215 s +## Fitted using 572 model solutions performed in 1.204 s ## ## Error model: Constant variance ## @@ -499,8 +499,8 @@ <div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb24-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(mm.L3[[<span class="st">"DFOP"</span>, <span class="dv">1</span>]])</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:16 2019 -## Date of summary: Wed Sep 18 18:24:16 2019 +## Date of fit: Thu Sep 19 09:53:04 2019 +## Date of summary: Thu Sep 19 09:53:04 2019 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * @@ -509,7 +509,7 @@ ## ## Model predictions using solution type analytical ## -## Fitted using 373 model solutions performed in 0.778 s +## Fitted using 373 model solutions performed in 0.799 s ## ## Error model: Constant variance ## @@ -605,15 +605,15 @@ <div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb29-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(mm.L4[[<span class="st">"SFO"</span>, <span class="dv">1</span>]], <span class="dt">data =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:17 2019 -## Date of summary: Wed Sep 18 18:24:17 2019 +## Date of fit: Thu Sep 19 09:53:04 2019 +## Date of summary: Thu Sep 19 09:53:05 2019 ## ## Equations: ## d_parent/dt = - k_parent_sink * parent ## ## Model predictions using solution type analytical ## -## Fitted using 142 model solutions performed in 0.293 s +## Fitted using 142 model solutions performed in 0.287 s ## ## Error model: Constant variance ## @@ -670,15 +670,15 @@ <div class="sourceCode" id="cb31"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb31-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/summary.html">summary</a></span>(mm.L4[[<span class="st">"FOMC"</span>, <span class="dv">1</span>]], <span class="dt">data =</span> <span class="ot">FALSE</span>)</a></code></pre></div> <pre><code>## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:17 2019 -## Date of summary: Wed Sep 18 18:24:17 2019 +## Date of fit: Thu Sep 19 09:53:05 2019 +## Date of summary: Thu Sep 19 09:53:05 2019 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 224 model solutions performed in 0.46 s +## Fitted using 224 model solutions performed in 0.48 s ## ## Error model: Constant variance ## diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html index 90549b0f..ec138595 100644 --- a/docs/articles/mkin.html +++ b/docs/articles/mkin.html @@ -90,7 +90,7 @@ <h1>Introduction to mkin</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>mkin.Rmd</code></div> diff --git a/docs/articles/twa.html b/docs/articles/twa.html index 2d44a89d..9cb5873a 100644 --- a/docs/articles/twa.html +++ b/docs/articles/twa.html @@ -90,7 +90,7 @@ <h1>Calculation of time weighted average concentrations with mkin</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>twa.Rmd</code></div> diff --git a/docs/articles/web_only/FOCUS_Z.html b/docs/articles/web_only/FOCUS_Z.html index aed1debc..5ea0b256 100644 --- a/docs/articles/web_only/FOCUS_Z.html +++ b/docs/articles/web_only/FOCUS_Z.html @@ -90,7 +90,7 @@ <h1>Example evaluation of FOCUS dataset Z</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>FOCUS_Z.Rmd</code></div> diff --git a/docs/articles/web_only/NAFTA_examples.html b/docs/articles/web_only/NAFTA_examples.html index 3ca93667..0476acf8 100644 --- a/docs/articles/web_only/NAFTA_examples.html +++ b/docs/articles/web_only/NAFTA_examples.html @@ -90,7 +90,7 @@ <h1>Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>NAFTA_examples.Rmd</code></div> diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html index d46e738a..c0682cb0 100644 --- a/docs/articles/web_only/benchmarks.html +++ b/docs/articles/web_only/benchmarks.html @@ -90,7 +90,7 @@ <h1>Benchmark timings for mkin on various systems</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>benchmarks.Rmd</code></div> @@ -204,77 +204,77 @@ ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.064 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.296 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 5.936 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 5.970 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 6.005 ## t2 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 11.019 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 22.889 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 12.558 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 21.239 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 20.545 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 36.524 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 37.266 ## t3 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 3.764 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.649 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.786 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.510 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.446 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.607 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.559 ## t4 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 14.347 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 13.789 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 8.461 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 13.805 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 15.335 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 31.617 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 31.574 ## t5 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 9.495 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 6.395 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.675 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.386 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 6.002 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 10.543 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 10.659 ## t6 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 2.623 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 2.542 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 2.723 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 2.643 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 2.635 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 2.579 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 2.634 ## t7 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 4.587 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.128 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.478 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.374 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.259 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.341 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.324 ## t8 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 7.525 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.632 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.862 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.02 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.737 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.101 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.233 ## t9 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 16.621 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 8.171 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.618 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 11.124 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 7.763 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 16.211 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 16.376 ## t10 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 8.576 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 3.676 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 3.579 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 5.388 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 3.427 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.041 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.058 ## t11 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 31.267 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 5.636 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.574 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.365 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 5.626 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 10.804</code></pre> +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 11.133</code></pre> <div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><a class="sourceLine" id="cb17-1" title="1"><span class="kw"><a href="https://rdrr.io/r/base/save.html">save</a></span>(mkin_benchmarks, <span class="dt">file =</span> <span class="st">"~/git/mkin/vignettes/mkin_benchmarks.rda"</span>)</a></code></pre></div> </div> </div> diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html index 1876e2b3..6df504ed 100644 --- a/docs/articles/web_only/compiled_models.html +++ b/docs/articles/web_only/compiled_models.html @@ -90,7 +90,7 @@ <h1>Performance benefit by using compiled model definitions in mkin</h1> <h4 class="author">Johannes Ranke</h4> - <h4 class="date">2019-09-18</h4> + <h4 class="date">2019-09-19</h4> <div class="hidden name"><code>compiled_models.Rmd</code></div> @@ -165,9 +165,9 @@ ## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet ## = TRUE): Observations with value of zero were removed from the data</code></pre> <pre><code>## test replications elapsed relative user.self sys.self -## 3 deSolve, compiled 3 3.129 1.000 3.127 0 -## 1 deSolve, not compiled 3 28.841 9.217 28.827 0 -## 2 Eigenvalue based 3 4.433 1.417 4.430 0 +## 3 deSolve, compiled 3 3.171 1.000 3.170 0 +## 1 deSolve, not compiled 3 29.012 9.149 28.996 0 +## 2 Eigenvalue based 3 4.473 1.411 4.470 0 ## user.child sys.child ## 3 0 0 ## 1 0 0 @@ -216,8 +216,8 @@ ## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with ## value of zero were removed from the data</code></pre> <pre><code>## test replications elapsed relative user.self sys.self -## 2 deSolve, compiled 3 4.860 1.000 4.857 0 -## 1 deSolve, not compiled 3 53.877 11.086 53.850 0 +## 2 deSolve, compiled 3 4.913 1.000 4.909 0 +## 1 deSolve, not compiled 3 53.418 10.873 53.393 0 ## user.child sys.child ## 2 0 0 ## 1 0 0</code></pre> diff --git a/docs/reference/index.html b/docs/reference/index.html index b86df636..a8b326d7 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -311,7 +311,7 @@ </tr><tr> <td> - <p><code><a href="synthetic_data_for_UBA.html">synthetic_data_for_UBA_2014</a></code> </p> + <p><code><a href="synthetic_data_for_UBA_2014.html">synthetic_data_for_UBA_2014</a></code> </p> </td> <td><p>Synthetic datasets for one parent compound with two metabolites</p></td> </tr><tr> diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index dc052f2a..0767d2f8 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -408,15 +408,15 @@ Per default, parameters in the kinetic models are internally transformed in <span class='no'>fit</span> <span class='kw'><-</span> <span class='fu'>mkinfit</span>(<span class='st'>"FOMC"</span>, <span class='no'>FOCUS_2006_C</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:06 2019 -#> Date of summary: Wed Sep 18 18:22:06 2019 +#> Date of fit: Thu Sep 19 09:50:54 2019 +#> Date of summary: Thu Sep 19 09:50:54 2019 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 222 model solutions performed in 0.459 s +#> Fitted using 222 model solutions performed in 0.458 s #> #> Error model: Constant variance #> @@ -490,7 +490,7 @@ Per default, parameters in the kinetic models are internally transformed in <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>))</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='co'># Fit the model to the FOCUS example dataset D using defaults</span> <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>fit</span> <span class='kw'><-</span> <span class='fu'>mkinfit</span>(<span class='no'>SFO_SFO</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>solution_type</span> <span class='kw'>=</span> <span class='st'>"eigen"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)))</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='output co'>#> User System verstrichen -#> 1.494 0.000 1.496 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#> NULL</div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#> $ff +#> 1.479 0.002 1.482 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#> NULL</div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -563,7 +563,7 @@ Per default, parameters in the kinetic models are internally transformed in #> Sum of squared residuals at call 126: 371.2134 #> Sum of squared residuals at call 135: 371.2134 #> Negative log-likelihood at call 145: 97.22429</div><div class='output co'>#> <span class='message'>Optimisation successfully terminated.</span></div><div class='output co'>#> User System verstrichen -#> 1.056 0.000 1.057 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>fit.deSolve</span>)</div><div class='output co'>#> NULL</div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span>(<span class='no'>fit.deSolve</span>)</div><div class='output co'>#> $ff +#> 1.053 0.000 1.054 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/coef.html'>coef</a></span>(<span class='no'>fit.deSolve</span>)</div><div class='output co'>#> NULL</div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span>(<span class='no'>fit.deSolve</span>)</div><div class='output co'>#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -599,8 +599,8 @@ Per default, parameters in the kinetic models are internally transformed in <span class='no'>SFO_SFO.ff</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"m1"</span>), <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='no'>f.noweight</span> <span class='kw'><-</span> <span class='fu'>mkinfit</span>(<span class='no'>SFO_SFO.ff</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>f.noweight</span>)</div><div class='output co'>#> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:22 2019 -#> Date of summary: Wed Sep 18 18:22:22 2019 +#> Date of fit: Thu Sep 19 09:51:10 2019 +#> Date of summary: Thu Sep 19 09:51:10 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -608,7 +608,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 421 model solutions performed in 1.15 s +#> Fitted using 421 model solutions performed in 1.138 s #> #> Error model: Constant variance #> @@ -718,8 +718,8 @@ Per default, parameters in the kinetic models are internally transformed in #> 120 m1 25.15 28.78984 -3.640e+00 #> 120 m1 33.31 28.78984 4.520e+00</div><div class='input'><span class='no'>f.obs</span> <span class='kw'><-</span> <span class='fu'>mkinfit</span>(<span class='no'>SFO_SFO.ff</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>error_model</span> <span class='kw'>=</span> <span class='st'>"obs"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>f.obs</span>)</div><div class='output co'>#> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:24 2019 -#> Date of summary: Wed Sep 18 18:22:24 2019 +#> Date of fit: Thu Sep 19 09:51:12 2019 +#> Date of summary: Thu Sep 19 09:51:12 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -727,7 +727,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 979 model solutions performed in 2.553 s +#> Fitted using 979 model solutions performed in 2.565 s #> #> Error model: Variance unique to each observed variable #> @@ -850,8 +850,8 @@ Per default, parameters in the kinetic models are internally transformed in #> 120 m1 25.15 28.80429 -3.654e+00 #> 120 m1 33.31 28.80429 4.506e+00</div><div class='input'><span class='no'>f.tc</span> <span class='kw'><-</span> <span class='fu'>mkinfit</span>(<span class='no'>SFO_SFO.ff</span>, <span class='no'>FOCUS_2006_D</span>, <span class='kw'>error_model</span> <span class='kw'>=</span> <span class='st'>"tc"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> <span class='warning'>Warning: Observations with value of zero were removed from the data</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>f.tc</span>)</div><div class='output co'>#> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:34 2019 -#> Date of summary: Wed Sep 18 18:22:34 2019 +#> Date of fit: Thu Sep 19 09:51:22 2019 +#> Date of summary: Thu Sep 19 09:51:22 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -859,7 +859,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 2289 model solutions performed in 9.369 s +#> Fitted using 2289 model solutions performed in 9.24 s #> #> Error model: Two-component variance function #> diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html index a5cdd04d..f592af1c 100644 --- a/docs/reference/mkinmod.html +++ b/docs/reference/mkinmod.html @@ -239,7 +239,7 @@ For the definition of model types and their parameters, the equations given <span class='no'>SFO_SFO</span> <span class='kw'><-</span> <span class='fu'>mkinmod</span>( <span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"m1"</span>), <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> Compilation argument: -#> /usr/lib/R/bin/R CMD SHLIB file310b6c1fede0.c 2> file310b6c1fede0.c.err.txt +#> /usr/lib/R/bin/R CMD SHLIB file663b71dc323f.c 2> file663b71dc323f.c.err.txt #> Program source: #> 1: #include <R.h> #> 2: diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html index 97d3ca3a..5faff3c7 100644 --- a/docs/reference/mkinpredict.html +++ b/docs/reference/mkinpredict.html @@ -332,17 +332,17 @@ <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fl'>0</span>), <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>20</span>, <span class='kw'>by</span> <span class='kw'>=</span> <span class='fl'>0.1</span>), <span class='kw'>solution_type</span> <span class='kw'>=</span> <span class='st'>"eigen"</span>)[<span class='fl'>201</span>,]))</div><div class='output co'>#> time parent m1 #> 201 20 4.978707 27.46227</div><div class='output co'>#> User System verstrichen -#> 0.003 0.000 0.004 </div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>( +#> 0.004 0.000 0.004 </div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>( <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='fu'>mkinpredict</span>(<span class='no'>SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent_m1</span> <span class='kw'>=</span> <span class='fl'>0.05</span>, <span class='kw'>k_parent_sink</span> <span class='kw'>=</span> <span class='fl'>0.1</span>, <span class='kw'>k_m1_sink</span> <span class='kw'>=</span> <span class='fl'>0.01</span>), <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fl'>0</span>), <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>20</span>, <span class='kw'>by</span> <span class='kw'>=</span> <span class='fl'>0.1</span>), <span class='kw'>solution_type</span> <span class='kw'>=</span> <span class='st'>"deSolve"</span>)[<span class='fl'>201</span>,]))</div><div class='output co'>#> time parent m1 #> 201 20 4.978707 27.46227</div><div class='output co'>#> User System verstrichen -#> 0.001 0.000 0.002 </div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>( +#> 0.002 0.000 0.002 </div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>( <span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='fu'>mkinpredict</span>(<span class='no'>SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent_m1</span> <span class='kw'>=</span> <span class='fl'>0.05</span>, <span class='kw'>k_parent_sink</span> <span class='kw'>=</span> <span class='fl'>0.1</span>, <span class='kw'>k_m1_sink</span> <span class='kw'>=</span> <span class='fl'>0.01</span>), <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>m1</span> <span class='kw'>=</span> <span class='fl'>0</span>), <span class='fu'><a href='https://rdrr.io/r/base/seq.html'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>20</span>, <span class='kw'>by</span> <span class='kw'>=</span> <span class='fl'>0.1</span>), <span class='kw'>solution_type</span> <span class='kw'>=</span> <span class='st'>"deSolve"</span>, <span class='kw'>use_compiled</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)[<span class='fl'>201</span>,]))</div><div class='output co'>#> time parent m1 #> 201 20 4.978707 27.46227</div><div class='output co'>#> User System verstrichen -#> 0.021 0.000 0.022 </div><div class='input'> +#> 0.022 0.000 0.021 </div><div class='input'> <span class='co'># \dontrun{</span> <span class='co'># Predict from a fitted model</span> <span class='no'>f</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='no'>FOCUS_2006_C</span>)</div><div class='output co'>#> <span class='message'>Ordinary least squares optimisation</span></div><div class='output co'>#> Sum of squared residuals at call 1: 552.5739 diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html index 81ebde7c..0f384062 100644 --- a/docs/reference/mmkin.html +++ b/docs/reference/mmkin.html @@ -199,8 +199,8 @@ <span class='no'>time_1</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>fits.4</span> <span class='kw'><-</span> <span class='fu'>mmkin</span>(<span class='no'>models</span>, <span class='no'>datasets</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)) <span class='no'>time_default</span></div><div class='output co'>#> User System verstrichen -#> 0.013 0.039 5.128 </div><div class='input'><span class='no'>time_1</span></div><div class='output co'>#> User System verstrichen -#> 18.942 0.000 18.951 </div><div class='input'> +#> 0.016 0.029 4.960 </div><div class='input'><span class='no'>time_1</span></div><div class='output co'>#> User System verstrichen +#> 19.084 0.004 19.099 </div><div class='input'> <span class='fu'><a href='endpoints.html'>endpoints</a></span>(<span class='no'>fits.0</span><span class='kw'>[[</span><span class='st'>"SFO_lin"</span>, <span class='fl'>2</span>]])</div><div class='output co'>#> $ff #> parent_M1 parent_sink M1_M2 M1_sink #> 0.7340481 0.2659519 0.7505684 0.2494316 diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html index c5d58911..73410181 100644 --- a/docs/reference/summary.mkinfit.html +++ b/docs/reference/summary.mkinfit.html @@ -215,15 +215,15 @@ <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> <pre class="examples"><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>)), <span class='no'>FOCUS_2006_A</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))</div><div class='output co'>#> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:23:52 2019 -#> Date of summary: Wed Sep 18 18:23:52 2019 +#> Date of fit: Thu Sep 19 09:52:40 2019 +#> Date of summary: Thu Sep 19 09:52:40 2019 #> #> Equations: #> d_parent/dt = - k_parent_sink * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 131 model solutions performed in 0.268 s +#> Fitted using 131 model solutions performed in 0.27 s #> #> Error model: Constant variance #> diff --git a/docs/reference/synthetic_data_for_UBA_2014-1.png b/docs/reference/synthetic_data_for_UBA_2014-1.png Binary files differnew file mode 100644 index 00000000..9d8c0931 --- /dev/null +++ b/docs/reference/synthetic_data_for_UBA_2014-1.png diff --git a/docs/reference/synthetic_data_for_UBA_2014.html b/docs/reference/synthetic_data_for_UBA_2014.html new file mode 100644 index 00000000..2c4480d9 --- /dev/null +++ b/docs/reference/synthetic_data_for_UBA_2014.html @@ -0,0 +1,462 @@ +<!-- Generated by pkgdown: do not edit by hand --> +<!DOCTYPE html> +<html lang="en"> + <head> + <meta charset="utf-8"> +<meta http-equiv="X-UA-Compatible" content="IE=edge"> +<meta name="viewport" content="width=device-width, initial-scale=1.0"> + +<title>Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014 • mkin</title> + +<!-- jquery --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js" integrity="sha256-FgpCb/KJQlLNfOu91ta32o/NMZxltwRo8QtmkMRdAu8=" crossorigin="anonymous"></script> +<!-- Bootstrap --> + +<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/css/bootstrap.min.css" integrity="sha256-916EbMg70RQy9LHiGkXzG8hSg9EdNy97GazNG/aiY1w=" crossorigin="anonymous" /> +<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha256-U5ZEeKfGNOja007MMD3YBI0A3OSZOQbeG6z2f2Y0hu8=" crossorigin="anonymous"></script> + +<!-- Font Awesome icons --> +<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.7.1/css/all.min.css" integrity="sha256-nAmazAk6vS34Xqo0BSrTb+abbtFlgsFK7NKSi6o7Y78=" crossorigin="anonymous" /> +<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.7.1/css/v4-shims.min.css" integrity="sha256-6qHlizsOWFskGlwVOKuns+D1nB6ssZrHQrNj1wGplHc=" crossorigin="anonymous" /> + +<!-- clipboard.js --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.4/clipboard.min.js" integrity="sha256-FiZwavyI2V6+EXO1U+xzLG3IKldpiTFf3153ea9zikQ=" crossorigin="anonymous"></script> + +<!-- headroom.js --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.9.4/headroom.min.js" integrity="sha256-DJFC1kqIhelURkuza0AvYal5RxMtpzLjFhsnVIeuk+U=" crossorigin="anonymous"></script> +<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.9.4/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script> + +<!-- pkgdown --> +<link href="../pkgdown.css" rel="stylesheet"> +<script src="../pkgdown.js"></script> + + + +<meta property="og:title" content="Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014" /> + +<meta property="og:description" content="The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites. +Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y. Note that this is a simplified version + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + measured values approximates lognormal distribution for high values, whereas we are using + normally distributed error components all along. +Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to NA. +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." /> +<meta name="twitter:card" content="summary" /> + + + +<!-- mathjax --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> +<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> + +<!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--> + + + + </head> + + <body> + <div class="container template-reference-topic"> + <header> + <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.9.49.6</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"> + <li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"> + <li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + </ul> +</li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul> + + <ul class="nav navbar-nav navbar-right"> + + </ul> + + </div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header> + +<div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Synthetic datasets for one parent compound with two metabolites</h1> + + <div class="hidden name"><code>synthetic_data_for_UBA_2014.Rd</code></div> + </div> + + <div class="ref-description"> + + <p>The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites.</p> +<p>Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y. Note that this is a simplified version + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + measured values approximates lognormal distribution for high values, whereas we are using + normally distributed error components all along.</p> +<p>Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to <code>NA</code>.</p> +<p>As an example, the first dataset has the title <code>SFO_lin_a</code> and is based on the SFO model + with two sequential metabolites (linear pathway), with added variance component 'a'.</p> +<p>Compare also the code in the example section to see the degradation models.</p> + + </div> + + <pre class="usage"><span class='no'>synthetic_data_for_UBA_2014</span></pre> + + <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2> + + <p>A list containing twelve datasets as an R6 class defined by <code><a href='mkinds.html'>mkinds</a></code>, + each containing, among others, the following components</p><dl class='dl-horizontal'> + <dt><code>title</code></dt><dd><p>The name of the dataset, e.g. <code>SFO_lin_a</code></p></dd> + <dt><code>data</code></dt><dd><p>A data frame with the data in the form expected by <code><a href='mkinfit.html'>mkinfit</a></code></p></dd> + +</dl> + + + <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2> + + <p>Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative + zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452</p> +<p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for + measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p> + + + <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> + <pre class="examples"><div class='input'><span class='co'># The data have been generated using the following kinetic models</span> +<span class='no'>m_synth_SFO_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M1"</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M2"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> + +<span class='no'>m_synth_SFO_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>), + <span class='kw'>sink</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> +<span class='no'>m_synth_DFOP_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"DFOP"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M1"</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M2"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> +<span class='no'>m_synth_DFOP_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"DFOP"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>), + <span class='kw'>sink</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), + <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> +<span class='co'># The model predictions without intentional error were generated as follows</span> +<span class='no'>sampling_times</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span>) + +<span class='no'>d_synth_SFO_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_synth_SFO_lin</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent</span> <span class='kw'>=</span> <span class='fl'>0.7</span>, <span class='kw'>f_parent_to_M1</span> <span class='kw'>=</span> <span class='fl'>0.8</span>, + <span class='kw'>k_M1</span> <span class='kw'>=</span> <span class='fl'>0.3</span>, <span class='kw'>f_M1_to_M2</span> <span class='kw'>=</span> <span class='fl'>0.7</span>, + <span class='kw'>k_M2</span> <span class='kw'>=</span> <span class='fl'>0.02</span>), + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fl'>0</span>, <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fl'>0</span>), + <span class='no'>sampling_times</span>) + +<span class='no'>d_synth_DFOP_lin</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_synth_DFOP_lin</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k1</span> <span class='kw'>=</span> <span class='fl'>0.2</span>, <span class='kw'>k2</span> <span class='kw'>=</span> <span class='fl'>0.02</span>, <span class='kw'>g</span> <span class='kw'>=</span> <span class='fl'>0.5</span>, + <span class='kw'>f_parent_to_M1</span> <span class='kw'>=</span> <span class='fl'>0.5</span>, <span class='kw'>k_M1</span> <span class='kw'>=</span> <span class='fl'>0.3</span>, + <span class='kw'>f_M1_to_M2</span> <span class='kw'>=</span> <span class='fl'>0.7</span>, <span class='kw'>k_M2</span> <span class='kw'>=</span> <span class='fl'>0.02</span>), + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fl'>0</span>, <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fl'>0</span>), + <span class='no'>sampling_times</span>) + +<span class='no'>d_synth_SFO_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_synth_SFO_par</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent</span> <span class='kw'>=</span> <span class='fl'>0.2</span>, + <span class='kw'>f_parent_to_M1</span> <span class='kw'>=</span> <span class='fl'>0.8</span>, <span class='kw'>k_M1</span> <span class='kw'>=</span> <span class='fl'>0.01</span>, + <span class='kw'>f_parent_to_M2</span> <span class='kw'>=</span> <span class='fl'>0.2</span>, <span class='kw'>k_M2</span> <span class='kw'>=</span> <span class='fl'>0.02</span>), + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fl'>0</span>, <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fl'>0</span>), + <span class='no'>sampling_times</span>) + +<span class='no'>d_synth_DFOP_par</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_synth_DFOP_par</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k1</span> <span class='kw'>=</span> <span class='fl'>0.3</span>, <span class='kw'>k2</span> <span class='kw'>=</span> <span class='fl'>0.02</span>, <span class='kw'>g</span> <span class='kw'>=</span> <span class='fl'>0.7</span>, + <span class='kw'>f_parent_to_M1</span> <span class='kw'>=</span> <span class='fl'>0.6</span>, <span class='kw'>k_M1</span> <span class='kw'>=</span> <span class='fl'>0.04</span>, + <span class='kw'>f_parent_to_M2</span> <span class='kw'>=</span> <span class='fl'>0.4</span>, <span class='kw'>k_M2</span> <span class='kw'>=</span> <span class='fl'>0.01</span>), + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fl'>0</span>, <span class='kw'>M2</span> <span class='kw'>=</span> <span class='fl'>0</span>), + <span class='no'>sampling_times</span>) + +<span class='co'># Construct names for datasets with errors</span> +<span class='no'>d_synth_names</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='st'>"d_synth_"</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"SFO_lin"</span>, <span class='st'>"SFO_par"</span>, + <span class='st'>"DFOP_lin"</span>, <span class='st'>"DFOP_par"</span>)) + +<span class='co'># Original function used or adding errors. The add_err function now published</span> +<span class='co'># with this package is a slightly generalised version where the names of</span> +<span class='co'># secondary compartments that should have an initial value of zero (M1 and M2</span> +<span class='co'># in this case) are not hardcoded any more.</span> +<span class='co'># add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789)</span> +<span class='co'># {</span> +<span class='co'># set.seed(seed)</span> +<span class='co'># d_long = mkin_wide_to_long(d, time = "time")</span> +<span class='co'># d_rep = data.frame(lapply(d_long, rep, each = 2))</span> +<span class='co'># d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value))</span> +<span class='co'>#</span> +<span class='co'># d_rep[d_rep$time == 0 & match(d_rep$name, c("M1", "M2"), "value"] <- 0</span> +<span class='co'># d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value))</span> +<span class='co'># d_NA$value <- round(d_NA$value, 1)</span> +<span class='co'># return(d_NA)</span> +<span class='co'># }</span> + +<span class='co'># The following is the simplified version of the two-component model of Rocke</span> +<span class='co'># and Lorenzato (1995)</span> +<span class='no'>sdfunc_twocomp</span> <span class='kw'>=</span> <span class='kw'>function</span>(<span class='no'>value</span>, <span class='no'>sd_low</span>, <span class='no'>rsd_high</span>) { + <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>sqrt</a></span>(<span class='no'>sd_low</span>^<span class='fl'>2</span> + <span class='no'>value</span>^<span class='fl'>2</span> * <span class='no'>rsd_high</span>^<span class='fl'>2</span>) +} + +<span class='co'># Add the errors.</span> +<span class='kw'>for</span> (<span class='no'>d_synth_name</span> <span class='kw'>in</span> <span class='no'>d_synth_names</span>) +{ + <span class='no'>d_synth</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/get.html'>get</a></span>(<span class='no'>d_synth_name</span>) + <span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='no'>d_synth_name</span>, <span class='st'>"_a"</span>), <span class='fu'><a href='add_err.html'>add_err</a></span>(<span class='no'>d_synth</span>, <span class='kw'>function</span>(<span class='no'>value</span>) <span class='fl'>3</span>)) + <span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='no'>d_synth_name</span>, <span class='st'>"_b"</span>), <span class='fu'><a href='add_err.html'>add_err</a></span>(<span class='no'>d_synth</span>, <span class='kw'>function</span>(<span class='no'>value</span>) <span class='fl'>7</span>)) + <span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste0</a></span>(<span class='no'>d_synth_name</span>, <span class='st'>"_c"</span>), <span class='fu'><a href='add_err.html'>add_err</a></span>(<span class='no'>d_synth</span>, + <span class='kw'>function</span>(<span class='no'>value</span>) <span class='fu'>sdfunc_twocomp</span>(<span class='no'>value</span>, <span class='fl'>0.5</span>, <span class='fl'>0.07</span>))) + +} + +<span class='no'>d_synth_err_names</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>( + <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/rep.html'>rep</a></span>(<span class='no'>d_synth_names</span>, <span class='kw'>each</span> <span class='kw'>=</span> <span class='fl'>3</span>), <span class='no'>letters</span>[<span class='fl'>1</span>:<span class='fl'>3</span>], <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>"_"</span>) +) + +<span class='co'># This is just one example of an evaluation using the kinetic model used for</span> +<span class='co'># the generation of the data</span> +<span class='no'>fit</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_SFO_lin</span>, <span class='no'>synthetic_data_for_UBA_2014</span><span class='kw'>[[</span><span class='fl'>1</span>]]$<span class='no'>data</span>, + <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span>(<span class='no'>fit</span>)</div><div class='img'><img src='synthetic_data_for_UBA_2014-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#> mkin version used for fitting: 0.9.49.6 +#> R version used for fitting: 3.6.1 +#> Date of fit: Thu Sep 19 12:43:02 2019 +#> Date of summary: Thu Sep 19 12:43:02 2019 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1 +#> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted using 847 model solutions performed in 2.51 s +#> +#> Error model: Constant variance +#> +#> Error model algorithm: OLS +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 101.350000 state +#> k_parent 0.100000 deparm +#> k_M1 0.100100 deparm +#> k_M2 0.100200 deparm +#> f_parent_to_M1 0.500000 deparm +#> f_M1_to_M2 0.500000 deparm +#> sigma 2.273126 error +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 101.350000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_M1 -2.301586 -Inf Inf +#> log_k_M2 -2.300587 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> f_M1_ilr_1 0.000000 -Inf Inf +#> sigma 2.273126 0 Inf +#> +#> Fixed parameter values: +#> value type +#> M1_0 0 state +#> M2_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 102.1000 1.57000 98.8600 105.3000 +#> log_k_parent -0.3020 0.03885 -0.3812 -0.2229 +#> log_k_M1 -1.2070 0.07123 -1.3520 -1.0620 +#> log_k_M2 -3.9010 0.06571 -4.0350 -3.7670 +#> f_parent_ilr_1 0.8492 0.16640 0.5103 1.1880 +#> f_M1_ilr_1 0.6780 0.17600 0.3196 1.0360 +#> sigma 2.2730 0.25740 1.7490 2.7970 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_M1 log_k_M2 f_parent_ilr_1 +#> parent_0 1.000e+00 3.933e-01 -1.605e-01 2.819e-02 -4.624e-01 +#> log_k_parent 3.933e-01 1.000e+00 -4.082e-01 7.166e-02 -5.682e-01 +#> log_k_M1 -1.605e-01 -4.082e-01 1.000e+00 -3.929e-01 7.478e-01 +#> 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 +#> 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 +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 102.10000 65.000 7.281e-36 98.86000 105.30000 +#> k_parent 0.73930 25.740 2.948e-23 0.68310 0.80020 +#> k_M1 0.29920 14.040 1.577e-15 0.25880 0.34590 +#> k_M2 0.02023 15.220 1.653e-16 0.01769 0.02312 +#> f_parent_to_M1 0.76870 18.370 7.295e-19 0.67300 0.84290 +#> f_M1_to_M2 0.72290 14.500 6.418e-16 0.61110 0.81240 +#> sigma 2.27300 8.832 2.161e-10 1.74900 2.79700 +#> +#> FOCUS Chi2 error levels in percent: +#> err.min n.optim df +#> All data 8.454 6 17 +#> parent 8.660 2 6 +#> M1 10.583 2 5 +#> M2 3.586 2 6 +#> +#> Resulting formation fractions: +#> ff +#> parent_M1 0.7687 +#> parent_sink 0.2313 +#> M1_M2 0.7229 +#> M1_sink 0.2771 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 0.9376 3.114 +#> M1 2.3170 7.697 +#> M2 34.2689 113.839 +#> +#> Data: +#> time variable observed predicted residual +#> 0 parent 101.5 1.021e+02 -0.56248 +#> 0 parent 101.2 1.021e+02 -0.86248 +#> 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 +#> 3 parent 7.6 1.111e+01 -3.50773 +#> 7 parent 1.1 5.772e-01 0.52283 +#> 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 +#> 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 +#> 3 M1 39.8 3.937e+01 0.42973 +#> 7 M1 15.1 1.549e+01 -0.38715 +#> 7 M1 17.8 1.549e+01 2.31285 +#> 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 +#> 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 +#> 7 M2 42.0 4.192e+01 0.07941 +#> 7 M2 43.1 4.192e+01 1.17941 +#> 14 M2 49.4 4.557e+01 3.83353 +#> 14 M2 44.3 4.557e+01 -1.26647 +#> 28 M2 34.6 3.547e+01 -0.87275 +#> 28 M2 33.0 3.547e+01 -2.47275 +#> 60 M2 18.8 1.858e+01 0.21837 +#> 60 M2 17.6 1.858e+01 -0.98163 +#> 90 M2 10.6 1.013e+01 0.47130 +#> 90 M2 10.8 1.013e+01 0.67130 +#> 120 M2 9.8 5.521e+00 4.27893 +#> 120 M2 3.3 5.521e+00 -2.22107</div></pre> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="sidebar"> + <h2>Contents</h2> + <ul class="nav nav-pills nav-stacked"> + + <li><a href="#format">Format</a></li> + + <li><a href="#source">Source</a></li> + + <li><a href="#examples">Examples</a></li> + </ul> + + </div> +</div> + + + <footer> + <div class="copyright"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.4.1.</p> +</div> + + </footer> + </div> + + + + + </body> +</html> + + diff --git a/docs/sitemap.xml b/docs/sitemap.xml index e75a0097..00d1a840 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -148,7 +148,7 @@ <loc>https://pkgdown.jrwb.de/mkin/reference/summary.mkinfit.html</loc> </url> <url> - <loc>https://pkgdown.jrwb.de/mkin/reference/synthetic_data_for_UBA.html</loc> + <loc>https://pkgdown.jrwb.de/mkin/reference/synthetic_data_for_UBA_2014.html</loc> </url> <url> <loc>https://pkgdown.jrwb.de/mkin/reference/test_data_from_UBA_2014.html</loc> diff --git a/man/synthetic_data_for_UBA_2014.Rd b/man/synthetic_data_for_UBA_2014.Rd index 4e10d209..2d726d5a 100644 --- a/man/synthetic_data_for_UBA_2014.Rd +++ b/man/synthetic_data_for_UBA_2014.Rd @@ -1,146 +1,146 @@ -\name{synthetic_data_for_UBA_2014} -\alias{synthetic_data_for_UBA_2014} -\docType{data} -\title{ - Synthetic datasets for one parent compound with two metabolites -} -\description{ - The 12 datasets were generated using four different models and three different - variance components. The four models are either the SFO or the DFOP model with either - two sequential or two parallel metabolites. - - Variance component 'a' is based on a normal distribution with standard deviation of 3, - Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. - Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the - minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 - for the increase of the standard deviation with y. Note that this is a simplified version - of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the - measured values approximates lognormal distribution for high values, whereas we are using - normally distributed error components all along. - - Initial concentrations for metabolites and all values where adding the variance component resulted - in a value below the assumed limit of detection of 0.1 were set to \code{NA}. - - As an example, the first dataset has the title \code{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. -} -\usage{synthetic_data_for_UBA_2014} -\format{ - A list containing twelve datasets as an R6 class defined by \code{\link{mkinds}}, - each containing, among others, the following components - \describe{ - \item{\code{title}}{The name of the dataset, e.g. \code{SFO_lin_a}} - \item{\code{data}}{A data frame with the data in the form expected by \code{\link{mkinfit}}} - } -} -\source{ - Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative - zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452 - - Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for - measurement error in analytical chemistry. Technometrics 37(2), 176-184. -} -\examples{ -# The data have been generated using the following kinetic models -m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"), - M1 = list(type = "SFO", to = "M2"), - M2 = list(type = "SFO"), use_of_ff = "max") - - -m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"), - sink = FALSE), - M1 = list(type = "SFO"), - M2 = list(type = "SFO"), use_of_ff = "max") - -m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"), - M1 = list(type = "SFO", to = "M2"), - M2 = list(type = "SFO"), use_of_ff = "max") - -m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"), - sink = FALSE), - M1 = list(type = "SFO"), - M2 = list(type = "SFO"), use_of_ff = "max") - -# The model predictions without intentional error were generated as follows -sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) - -d_synth_SFO_lin <- mkinpredict(m_synth_SFO_lin, - c(k_parent = 0.7, f_parent_to_M1 = 0.8, - k_M1 = 0.3, f_M1_to_M2 = 0.7, - k_M2 = 0.02), - c(parent = 100, M1 = 0, M2 = 0), - sampling_times) - -d_synth_DFOP_lin <- mkinpredict(m_synth_DFOP_lin, - c(k1 = 0.2, k2 = 0.02, g = 0.5, - f_parent_to_M1 = 0.5, k_M1 = 0.3, - f_M1_to_M2 = 0.7, k_M2 = 0.02), - c(parent = 100, M1 = 0, M2 = 0), - sampling_times) - -d_synth_SFO_par <- mkinpredict(m_synth_SFO_par, - c(k_parent = 0.2, - f_parent_to_M1 = 0.8, k_M1 = 0.01, - f_parent_to_M2 = 0.2, k_M2 = 0.02), - c(parent = 100, M1 = 0, M2 = 0), - sampling_times) - -d_synth_DFOP_par <- mkinpredict(m_synth_DFOP_par, - c(k1 = 0.3, k2 = 0.02, g = 0.7, - f_parent_to_M1 = 0.6, k_M1 = 0.04, - f_parent_to_M2 = 0.4, k_M2 = 0.01), - c(parent = 100, M1 = 0, M2 = 0), - sampling_times) - -# Construct names for datasets with errors -d_synth_names = paste0("d_synth_", c("SFO_lin", "SFO_par", - "DFOP_lin", "DFOP_par")) - -# Original function used or adding errors. The add_err function now published -# with this package is a slightly generalised version where the names of -# secondary compartments that should have an initial value of zero (M1 and M2 -# in this case) are not hardcoded any more. -# add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789) -# { -# set.seed(seed) -# d_long = mkin_wide_to_long(d, time = "time") -# d_rep = data.frame(lapply(d_long, rep, each = 2)) -# d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value)) -# -# d_rep[d_rep$time == 0 & match(d_rep$name, c("M1", "M2"), "value"] <- 0 -# d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value)) -# d_NA$value <- round(d_NA$value, 1) -# return(d_NA) -# } - -# The following is the simplified version of the two-component model of Rocke -# and Lorenzato (1995) -sdfunc_twocomp = function(value, sd_low, rsd_high) { - sqrt(sd_low^2 + value^2 * rsd_high^2) -} - -# Add the errors. -for (d_synth_name in d_synth_names) -{ - d_synth = get(d_synth_name) - assign(paste0(d_synth_name, "_a"), add_err(d_synth, function(value) 3)) - assign(paste0(d_synth_name, "_b"), add_err(d_synth, function(value) 7)) - assign(paste0(d_synth_name, "_c"), add_err(d_synth, - function(value) sdfunc_twocomp(value, 0.5, 0.07))) - -} - -d_synth_err_names = c( - paste(rep(d_synth_names, each = 3), letters[1:3], sep = "_") -) - -# This is just one example of an evaluation using the kinetic model used for -# 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) -} -\keyword{datasets} +\name{synthetic_data_for_UBA_2014}
+\alias{synthetic_data_for_UBA_2014}
+\docType{data}
+\title{
+ Synthetic datasets for one parent compound with two metabolites
+}
+\description{
+ The 12 datasets were generated using four different models and three different
+ variance components. The four models are either the SFO or the DFOP model with either
+ two sequential or two parallel metabolites.
+
+ Variance component 'a' is based on a normal distribution with standard deviation of 3,
+ Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
+ Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
+ minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
+ for the increase of the standard deviation with y. Note that this is a simplified version
+ of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the
+ measured values approximates lognormal distribution for high values, whereas we are using
+ normally distributed error components all along.
+
+ Initial concentrations for metabolites and all values where adding the variance component resulted
+ in a value below the assumed limit of detection of 0.1 were set to \code{NA}.
+
+ As an example, the first dataset has the title \code{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.
+}
+\usage{synthetic_data_for_UBA_2014}
+\format{
+ A list containing twelve datasets as an R6 class defined by \code{\link{mkinds}},
+ each containing, among others, the following components
+ \describe{
+ \item{\code{title}}{The name of the dataset, e.g. \code{SFO_lin_a}}
+ \item{\code{data}}{A data frame with the data in the form expected by \code{\link{mkinfit}}}
+ }
+}
+\source{
+ Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
+ zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452
+
+ Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
+ measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+}
+\examples{
+# The data have been generated using the following kinetic models
+m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
+ M1 = list(type = "SFO", to = "M2"),
+ M2 = list(type = "SFO"), use_of_ff = "max")
+
+
+m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"),
+ sink = FALSE),
+ M1 = list(type = "SFO"),
+ M2 = list(type = "SFO"), use_of_ff = "max")
+
+m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"),
+ M1 = list(type = "SFO", to = "M2"),
+ M2 = list(type = "SFO"), use_of_ff = "max")
+
+m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"),
+ sink = FALSE),
+ M1 = list(type = "SFO"),
+ M2 = list(type = "SFO"), use_of_ff = "max")
+
+# The model predictions without intentional error were generated as follows
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+
+d_synth_SFO_lin <- mkinpredict(m_synth_SFO_lin,
+ c(k_parent = 0.7, f_parent_to_M1 = 0.8,
+ k_M1 = 0.3, f_M1_to_M2 = 0.7,
+ k_M2 = 0.02),
+ c(parent = 100, M1 = 0, M2 = 0),
+ sampling_times)
+
+d_synth_DFOP_lin <- mkinpredict(m_synth_DFOP_lin,
+ c(k1 = 0.2, k2 = 0.02, g = 0.5,
+ f_parent_to_M1 = 0.5, k_M1 = 0.3,
+ f_M1_to_M2 = 0.7, k_M2 = 0.02),
+ c(parent = 100, M1 = 0, M2 = 0),
+ sampling_times)
+
+d_synth_SFO_par <- mkinpredict(m_synth_SFO_par,
+ c(k_parent = 0.2,
+ f_parent_to_M1 = 0.8, k_M1 = 0.01,
+ f_parent_to_M2 = 0.2, k_M2 = 0.02),
+ c(parent = 100, M1 = 0, M2 = 0),
+ sampling_times)
+
+d_synth_DFOP_par <- mkinpredict(m_synth_DFOP_par,
+ c(k1 = 0.3, k2 = 0.02, g = 0.7,
+ f_parent_to_M1 = 0.6, k_M1 = 0.04,
+ f_parent_to_M2 = 0.4, k_M2 = 0.01),
+ c(parent = 100, M1 = 0, M2 = 0),
+ sampling_times)
+
+# Construct names for datasets with errors
+d_synth_names = paste0("d_synth_", c("SFO_lin", "SFO_par",
+ "DFOP_lin", "DFOP_par"))
+
+# Original function used or adding errors. The add_err function now published
+# with this package is a slightly generalised version where the names of
+# secondary compartments that should have an initial value of zero (M1 and M2
+# in this case) are not hardcoded any more.
+# add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789)
+# {
+# set.seed(seed)
+# d_long = mkin_wide_to_long(d, time = "time")
+# d_rep = data.frame(lapply(d_long, rep, each = 2))
+# d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value))
+#
+# d_rep[d_rep$time == 0 & match(d_rep$name, c("M1", "M2"), "value"] <- 0
+# d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value))
+# d_NA$value <- round(d_NA$value, 1)
+# return(d_NA)
+# }
+
+# The following is the simplified version of the two-component model of Rocke
+# and Lorenzato (1995)
+sdfunc_twocomp = function(value, sd_low, rsd_high) {
+ sqrt(sd_low^2 + value^2 * rsd_high^2)
+}
+
+# Add the errors.
+for (d_synth_name in d_synth_names)
+{
+ d_synth = get(d_synth_name)
+ assign(paste0(d_synth_name, "_a"), add_err(d_synth, function(value) 3))
+ assign(paste0(d_synth_name, "_b"), add_err(d_synth, function(value) 7))
+ assign(paste0(d_synth_name, "_c"), add_err(d_synth,
+ function(value) sdfunc_twocomp(value, 0.5, 0.07)))
+
+}
+
+d_synth_err_names = c(
+ paste(rep(d_synth_names, each = 3), letters[1:3], sep = "_")
+)
+
+# This is just one example of an evaluation using the kinetic model used for
+# the generation of the data
+fit <- mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data,
+ quiet = TRUE)
+plot_sep(fit)
+summary(fit)
+}
+\keyword{datasets}
diff --git a/vignettes/mkin_benchmarks.rda b/vignettes/mkin_benchmarks.rda Binary files differindex aa794a02..bf9aec62 100644 --- a/vignettes/mkin_benchmarks.rda +++ b/vignettes/mkin_benchmarks.rda |
