diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2022-11-18 19:23:56 +0100 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2022-11-18 19:23:56 +0100 |
| commit | 317fd7514e638780c09ed6349a165a854ba2deea (patch) | |
| tree | 78130cf3da48fb6038e213d39a25e520dd61e21f /docs/reference | |
| parent | 5364f037a72863ef5ba81e14ba4417f68fd389f9 (diff) | |
Update docs
Diffstat (limited to 'docs/reference')
| -rw-r--r-- | docs/reference/Rplot001.png | bin | 14083 -> 22432 bytes | |||
| -rw-r--r-- | docs/reference/Rplot002.png | bin | 13699 -> 16953 bytes | |||
| -rw-r--r-- | docs/reference/ds_mixed-1.png | bin | 0 -> 219939 bytes | |||
| -rw-r--r-- | docs/reference/ds_mixed.html | 240 | ||||
| -rw-r--r-- | docs/reference/index.html | 10 | ||||
| -rw-r--r-- | docs/reference/parplot.html | 8 | ||||
| -rw-r--r-- | docs/reference/saem.html | 12 |
7 files changed, 260 insertions, 10 deletions
diff --git a/docs/reference/Rplot001.png b/docs/reference/Rplot001.png Binary files differindex ca982688..b3448db0 100644 --- a/docs/reference/Rplot001.png +++ b/docs/reference/Rplot001.png diff --git a/docs/reference/Rplot002.png b/docs/reference/Rplot002.png Binary files differindex de2d61aa..27feab09 100644 --- a/docs/reference/Rplot002.png +++ b/docs/reference/Rplot002.png diff --git a/docs/reference/ds_mixed-1.png b/docs/reference/ds_mixed-1.png Binary files differnew file mode 100644 index 00000000..a7f5c395 --- /dev/null +++ b/docs/reference/ds_mixed-1.png diff --git a/docs/reference/ds_mixed.html b/docs/reference/ds_mixed.html new file mode 100644 index 00000000..64b02749 --- /dev/null +++ b/docs/reference/ds_mixed.html @@ -0,0 +1,240 @@ +<!DOCTYPE html> +<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta 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href="../pkgdown.css" rel="stylesheet"><script src="../pkgdown.js"></script><meta property="og:title" content="Synthetic data for hierarchical kinetic degradation models — ds_mixed"><meta property="og:description" content="The R code used to create this data object is installed with this package in +the 'dataset_generation' directory."><!-- 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 data-spy="scroll" data-target="#toc"> + + + <div class="container 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name"><code>ds_mixed.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The R code used to create this data object is installed with this package in +the 'dataset_generation' directory.</p> + </div> + + + + <div id="ref-examples"> + <h2>Examples</h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span> <span class="va">sfo_mmkin</span> <span class="op"><-</span> <span class="fu"><a href="mmkin.html">mmkin</a></span><span class="op">(</span><span class="st">"SFO"</span>, <span class="va">ds_sfo</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>, cores <span class="op">=</span> <span class="fl">15</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="va">sfo_saem</span> <span class="op"><-</span> <span class="fu"><a href="saem.html">saem</a></span><span class="op">(</span><span class="va">sfo_mmkin</span>, no_random_effect <span class="op">=</span> <span class="st">"parent_0"</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/graphics/plot.default.html" class="external-link">plot</a></span><span class="op">(</span><span class="va">sfo_saem</span><span class="op">)</span></span></span> +<span class="r-plt img"><img src="ds_mixed-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span><span class="co"># }</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># This is the code used to generate the datasets</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/cat.html" class="external-link">cat</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/readLines.html" class="external-link">readLines</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/system.file.html" class="external-link">system.file</a></span><span class="op">(</span><span class="st">"dataset_generation/ds_mixed.R"</span>, package <span class="op">=</span> <span class="st">"mkin"</span><span class="op">)</span><span class="op">)</span>, sep <span class="op">=</span> <span class="st">"\n"</span><span class="op">)</span></span></span> +<span class="r-out co"><span class="r-pr">#></span> # Synthetic data for hierarchical kinetic models</span> +<span class="r-out co"><span class="r-pr">#></span> # Refactored version of the code previously in tests/testthat/setup_script.R</span> +<span class="r-out co"><span class="r-pr">#></span> # The number of datasets was 3 for FOMC, and 10 for HS in that script, now it</span> +<span class="r-out co"><span class="r-pr">#></span> # is always 15 for consistency</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> library(mkin) # We use mkinmod and mkinpredict</span> +<span class="r-out co"><span class="r-pr">#></span> sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)</span> +<span class="r-out co"><span class="r-pr">#></span> n <- 15</span> +<span class="r-out co"><span class="r-pr">#></span> log_sd <- 0.3</span> +<span class="r-out co"><span class="r-pr">#></span> err_1 = list(const = 1, prop = 0.05)</span> +<span class="r-out co"><span class="r-pr">#></span> tc <- function(value) sigma_twocomp(value, err_1$const, err_1$prop)</span> +<span class="r-out co"><span class="r-pr">#></span> const <- function(value) 2</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> SFO <- mkinmod(parent = mkinsub("SFO"))</span> +<span class="r-out co"><span class="r-pr">#></span> sfo_pop <- list(parent_0 = 100, k_parent = 0.03)</span> +<span class="r-out co"><span class="r-pr">#></span> sfo_parms <- as.matrix(data.frame(</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent = rlnorm(n, log(sfo_pop$k_parent), log_sd)))</span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> ds_sfo <- lapply(1:n, function(i) {</span> +<span class="r-out co"><span class="r-pr">#></span> ds_mean <- mkinpredict(SFO, sfo_parms[i, ],</span> +<span class="r-out co"><span class="r-pr">#></span> c(parent = sfo_pop$parent_0), sampling_times)</span> +<span class="r-out co"><span class="r-pr">#></span> add_err(ds_mean, tc, n = 1)[[1]]</span> +<span class="r-out co"><span class="r-pr">#></span> })</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_sfo, "pop") <- sfo_pop</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_sfo, "parms") <- sfo_parms</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> FOMC <- mkinmod(parent = mkinsub("FOMC"))</span> +<span class="r-out co"><span class="r-pr">#></span> fomc_pop <- list(parent_0 = 100, alpha = 2, beta = 8)</span> +<span class="r-out co"><span class="r-pr">#></span> fomc_parms <- as.matrix(data.frame(</span> +<span class="r-out co"><span class="r-pr">#></span> alpha = rlnorm(n, log(fomc_pop$alpha), 0.4),</span> +<span class="r-out co"><span class="r-pr">#></span> beta = rlnorm(n, log(fomc_pop$beta), 0.2)))</span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> ds_fomc <- lapply(1:n, function(i) {</span> +<span class="r-out co"><span class="r-pr">#></span> ds_mean <- mkinpredict(FOMC, fomc_parms[i, ],</span> +<span class="r-out co"><span class="r-pr">#></span> c(parent = fomc_pop$parent_0), sampling_times)</span> +<span class="r-out co"><span class="r-pr">#></span> add_err(ds_mean, tc, n = 1)[[1]]</span> +<span class="r-out co"><span class="r-pr">#></span> })</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_fomc, "pop") <- fomc_pop</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_fomc, "parms") <- fomc_parms</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> DFOP <- mkinmod(parent = mkinsub("DFOP"))</span> +<span class="r-out co"><span class="r-pr">#></span> dfop_pop <- list(parent_0 = 100, k1 = 0.06, k2 = 0.015, g = 0.4)</span> +<span class="r-out co"><span class="r-pr">#></span> dfop_parms <- as.matrix(data.frame(</span> +<span class="r-out co"><span class="r-pr">#></span> k1 = rlnorm(n, log(dfop_pop$k1), log_sd),</span> +<span class="r-out co"><span class="r-pr">#></span> k2 = rlnorm(n, log(dfop_pop$k2), log_sd),</span> +<span class="r-out co"><span class="r-pr">#></span> g = plogis(rnorm(n, qlogis(dfop_pop$g), log_sd))))</span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> ds_dfop <- lapply(1:n, function(i) {</span> +<span class="r-out co"><span class="r-pr">#></span> ds_mean <- mkinpredict(DFOP, dfop_parms[i, ],</span> +<span class="r-out co"><span class="r-pr">#></span> c(parent = dfop_pop$parent_0), sampling_times)</span> +<span class="r-out co"><span class="r-pr">#></span> add_err(ds_mean, tc, n = 1)[[1]]</span> +<span class="r-out co"><span class="r-pr">#></span> })</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_dfop, "pop") <- dfop_pop</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_dfop, "parms") <- dfop_parms</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> HS <- mkinmod(parent = mkinsub("HS"))</span> +<span class="r-out co"><span class="r-pr">#></span> hs_pop <- list(parent_0 = 100, k1 = 0.08, k2 = 0.01, tb = 15)</span> +<span class="r-out co"><span class="r-pr">#></span> hs_parms <- as.matrix(data.frame(</span> +<span class="r-out co"><span class="r-pr">#></span> k1 = rlnorm(n, log(hs_pop$k1), log_sd),</span> +<span class="r-out co"><span class="r-pr">#></span> k2 = rlnorm(n, log(hs_pop$k2), log_sd),</span> +<span class="r-out co"><span class="r-pr">#></span> tb = rlnorm(n, log(hs_pop$tb), 0.1)))</span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> ds_hs <- lapply(1:n, function(i) {</span> +<span class="r-out co"><span class="r-pr">#></span> ds_mean <- mkinpredict(HS, hs_parms[i, ],</span> +<span class="r-out co"><span class="r-pr">#></span> c(parent = hs_pop$parent_0), sampling_times)</span> +<span class="r-out co"><span class="r-pr">#></span> add_err(ds_mean, const, n = 1)[[1]]</span> +<span class="r-out co"><span class="r-pr">#></span> })</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_hs, "pop") <- hs_pop</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_hs, "parms") <- hs_parms</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> DFOP_SFO <- mkinmod(</span> +<span class="r-out co"><span class="r-pr">#></span> parent = mkinsub("DFOP", "m1"),</span> +<span class="r-out co"><span class="r-pr">#></span> m1 = mkinsub("SFO"),</span> +<span class="r-out co"><span class="r-pr">#></span> quiet = TRUE)</span> +<span class="r-out co"><span class="r-pr">#></span> dfop_sfo_pop <- list(parent_0 = 100,</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 = 0.007, f_parent_to_m1 = 0.5,</span> +<span class="r-out co"><span class="r-pr">#></span> k1 = 0.1, k2 = 0.02, g = 0.5)</span> +<span class="r-out co"><span class="r-pr">#></span> dfop_sfo_parms <- as.matrix(data.frame(</span> +<span class="r-out co"><span class="r-pr">#></span> k1 = rlnorm(n, log(dfop_sfo_pop$k1), log_sd),</span> +<span class="r-out co"><span class="r-pr">#></span> k2 = rlnorm(n, log(dfop_sfo_pop$k2), log_sd),</span> +<span class="r-out co"><span class="r-pr">#></span> g = plogis(rnorm(n, qlogis(dfop_sfo_pop$g), log_sd)),</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 = plogis(rnorm(n,</span> +<span class="r-out co"><span class="r-pr">#></span> qlogis(dfop_sfo_pop$f_parent_to_m1), log_sd)),</span> +<span class="r-out co"><span class="r-pr">#></span> k_m1 = rlnorm(n, log(dfop_sfo_pop$k_m1), log_sd)))</span> +<span class="r-out co"><span class="r-pr">#></span> ds_dfop_sfo_mean <- lapply(1:n,</span> +<span class="r-out co"><span class="r-pr">#></span> function(i) {</span> +<span class="r-out co"><span class="r-pr">#></span> mkinpredict(DFOP_SFO, dfop_sfo_parms[i, ],</span> +<span class="r-out co"><span class="r-pr">#></span> c(parent = dfop_sfo_pop$parent_0, m1 = 0), sampling_times)</span> +<span class="r-out co"><span class="r-pr">#></span> }</span> +<span class="r-out co"><span class="r-pr">#></span> )</span> +<span class="r-out co"><span class="r-pr">#></span> set.seed(123456)</span> +<span class="r-out co"><span class="r-pr">#></span> ds_dfop_sfo <- lapply(ds_dfop_sfo_mean, function(ds) {</span> +<span class="r-out co"><span class="r-pr">#></span> add_err(ds,</span> +<span class="r-out co"><span class="r-pr">#></span> sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),</span> +<span class="r-out co"><span class="r-pr">#></span> n = 1, secondary = "m1")[[1]]</span> +<span class="r-out co"><span class="r-pr">#></span> })</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_dfop_sfo, "pop") <- dfop_sfo_pop</span> +<span class="r-out co"><span class="r-pr">#></span> attr(ds_dfop_sfo, "parms") <- dfop_sfo_parms</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> #save(ds_sfo, ds_fomc, ds_dfop, ds_hs, ds_dfop_sfo, file = "data/ds_mixed.rda", version = 2)</span> +</code></pre></div> + </div> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"><h2 data-toc-skip>Contents</h2> + </nav></div> +</div> + + + <footer><div class="copyright"> + <p></p><p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> +</div> + + </footer></div> + + + + + + + </body></html> + diff --git a/docs/reference/index.html b/docs/reference/index.html index 665912f7..9fddf541 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -17,7 +17,7 @@ </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">1.2.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.2.1</span> </span> </div> @@ -268,9 +268,9 @@ degradation models and one or more error models</p></td> <p class="section-desc"></p> </th> </tr></tbody><tbody><tr><td> - <p><code><a href="focus_soil_moisture.html">focus_soil_moisture</a></code> </p> + <p><code><a href="ds_mixed.html">ds_mixed</a></code> <code><a href="ds_mixed.html">ds_sfo</a></code> <code><a href="ds_mixed.html">ds_fomc</a></code> <code><a href="ds_mixed.html">ds_dfop</a></code> <code><a href="ds_mixed.html">ds_hs</a></code> <code><a href="ds_mixed.html">ds_dfop_sfo</a></code> </p> </td> - <td><p>FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar</p></td> + <td><p>Synthetic data for hierarchical kinetic degradation models</p></td> </tr><tr><td> <p><code><a href="D24_2014.html">D24_2014</a></code> </p> </td> @@ -328,6 +328,10 @@ degradation models and one or more error models</p></td> </td> <td><p>Three experimental datasets from two water sediment systems and one soil</p></td> </tr><tr><td> + <p><code><a href="focus_soil_moisture.html">focus_soil_moisture</a></code> </p> + </td> + <td><p>FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar</p></td> + </tr><tr><td> <p><code><a href="mkinds.html">print(<i><mkinds></i>)</a></code> </p> </td> <td><p>A dataset class for mkin</p></td> diff --git a/docs/reference/parplot.html b/docs/reference/parplot.html index f4f3c811..ab02cbb3 100644 --- a/docs/reference/parplot.html +++ b/docs/reference/parplot.html @@ -19,7 +19,7 @@ or by their medians as proposed in the paper by Duchesne et al. (2021)."><!-- ma </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">1.2.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.2.1</span> </span> </div> @@ -137,6 +137,12 @@ If 'median', parameters are scaled using the median parameters from all fits.</p <dd><p>Title of the plot</p></dd> </dl></div> + <div id="details"> + <h2>Details</h2> + <p>Starting values of degradation model parameters and error model parameters +are shown as green circles. The results obtained in the original run +are shown as red circles.</p> + </div> <div id="references"> <h2>References</h2> <p>Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical diff --git a/docs/reference/saem.html b/docs/reference/saem.html index 5e7e0861..957c098e 100644 --- a/docs/reference/saem.html +++ b/docs/reference/saem.html @@ -19,7 +19,7 @@ Expectation Maximisation algorithm (SAEM)."><!-- mathjax --><script src="https:/ </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">1.2.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.2.1</span> </span> </div> @@ -113,7 +113,7 @@ Expectation Maximisation algorithm (SAEM).</p> <span> covariates <span class="op">=</span> <span class="cn">NULL</span>,</span> <span> covariate_models <span class="op">=</span> <span class="cn">NULL</span>,</span> <span> no_random_effect <span class="op">=</span> <span class="cn">NULL</span>,</span> -<span> error.init <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">3</span>, <span class="fl">0.1</span><span class="op">)</span>,</span> +<span> error.init <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">1</span><span class="op">)</span>,</span> <span> nbiter.saemix <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="fl">300</span>, <span class="fl">100</span><span class="op">)</span>,</span> <span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>displayProgress <span class="op">=</span> <span class="cn">FALSE</span>, print <span class="op">=</span> <span class="cn">FALSE</span>, nbiter.saemix <span class="op">=</span> <span class="va">nbiter.saemix</span>,</span> <span> save <span class="op">=</span> <span class="cn">FALSE</span>, save.graphs <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span> @@ -430,10 +430,10 @@ using <a href="mmkin.html">mmkin</a>.</p> <span class="r-plt img"><img src="saem-4.png" alt="" width="700" height="433"></span> <span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">f_saem_dfop_sfo</span>, data <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> saemix version used for fitting: 3.2 </span> -<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.2.0 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for pre-fitting: 1.2.1 </span> <span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.2 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Thu Nov 17 14:03:17 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Thu Nov 17 14:03:17 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Nov 18 19:19:25 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Nov 18 19:19:25 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *</span> @@ -448,7 +448,7 @@ using <a href="mmkin.html">mmkin</a>.</p> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted in 8.829 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted in 9.068 s</span> <span class="r-out co"><span class="r-pr">#></span> Using 300, 100 iterations and 10 chains</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Variance model: Constant variance </span> |
