Fix a bug for nlme with parent only, improve examples

13 files changed, 32 insertions, 150 deletions

diff --git a/R/nlme.mmkin.R b/R/nlme.mmkin.R
index d4720e79..22a70f18 100644
--- a/R/nlme.mmkin.R
+++ b/R/nlme.mmkin.R
@@ -53,6 +53,7 @@ get_deg_func <- function() {
 #' f_nlme_dfop <- nlme(f["DFOP", ])
 #' AIC(f_nlme_sfo, f_nlme_dfop)
 #' print(f_nlme_dfop)
+#' plot(f_nlme_dfop)
 #' endpoints(f_nlme_dfop)
 #' \dontrun{
 #'   f_nlme_2 <- nlme(f["SFO", ], start = c(parent_0 = 100, log_k_parent = 0.1))
@@ -63,58 +64,36 @@ get_deg_func <- function() {
 #'     A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE)
 #'   m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
 #'     A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
-#'   m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-#'     A1 = mkinsub("SFO"), quiet = TRUE)
 #'   m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
 #'     A1 = mkinsub("SFO"), quiet = TRUE)
 #'
 #'   f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo,
 #'    "SFO-SFO-ff" = m_sfo_sfo_ff,
-#'    "FOMC-SFO" = m_fomc_sfo,
 #'    "DFOP-SFO" = m_dfop_sfo),
 #'     ds_2, quiet = TRUE)
-#'   plot(f_2["SFO-SFO", 3:4]) # Separate fits for datasets 3 and 4
 #'
 #'   f_nlme_sfo_sfo <- nlme(f_2["SFO-SFO", ])
-#'   # plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures
-#'   plot(f_nlme_sfo_sfo, 3:4) # Global mixed model: Fits for datasets 3 and 4
+#'   plot(f_nlme_sfo_sfo)
 #'
 #'   # With formation fractions
 #'   f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
-#'   plot(f_nlme_sfo_sfo_ff, 3:4) # chi2 different due to different df attribution
+#'   plot(f_nlme_sfo_sfo_ff)
 #'
-#'   # For more parameters, we need to increase pnlsMaxIter and the tolerance
+#'   # For the following fit we need to increase pnlsMaxIter and the tolerance
 #'   # to get convergence
-#'   f_nlme_fomc_sfo <- nlme(f_2["FOMC-SFO", ],
-#'     control = list(pnlsMaxIter = 100, tolerance = 1e-4), verbose = TRUE)
 #'   f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
 #'     control = list(pnlsMaxIter = 120, tolerance = 5e-4), verbose = TRUE)
-#'   plot(f_2["FOMC-SFO", 3:4])
-#'   plot(f_nlme_fomc_sfo, 3:4)
 #'
-#'   plot(f_2["DFOP-SFO", 3:4])
-#'   plot(f_nlme_dfop_sfo, 3:4)
+#'   plot(f_nlme_dfop_sfo)
 #'
-#'   anova(f_nlme_dfop_sfo, f_nlme_fomc_sfo, f_nlme_sfo_sfo)
-#'   anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo) # if we ignore FOMC
+#'   anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo)
 #'
 #'   endpoints(f_nlme_sfo_sfo)
 #'   endpoints(f_nlme_dfop_sfo)
 #'
 #'   if (length(findFunction("varConstProp")) > 0) { # tc error model for nlme available
-#'     # Attempts to fit metabolite kinetics with the tc error model
-#'     #f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo,
-#'     #  "SFO-SFO-ff" = m_sfo_sfo_ff,
-#'     #  "FOMC-SFO" = m_fomc_sfo,
-#'     #  "DFOP-SFO" = m_dfop_sfo),
-#'     #   ds_2, quiet = TRUE,
-#'     #   error_model = "tc")
-#'     #f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ], control = list(maxIter = 100))
-#'     #f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ])
-#'     #f_nlme_dfop_sfo_tc <- update(f_nlme_dfop_sfo, weights = varConstProp(),
-#'     #  control = list(sigma = 1, msMaxIter = 100, pnlsMaxIter = 15))
-#'     # Fitting metabolite kinetics with nlme.mmkin and the two-component
-#'     # error model currently does not work, at least not with these data.
+#'     # Attempts to fit metabolite kinetics with the tc error model are possible,
+#'     # but need tweeking of control values and sometimes do not converge
 #'
 #'     f_tc <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, error_model = "tc")
 #'     f_nlme_sfo_tc <- nlme(f_tc["SFO", ])
diff --git a/R/plot.nlme.mmkin.R b/R/plot.nlme.mmkin.R
index 2356070e..223aba68 100644
--- a/R/plot.nlme.mmkin.R
+++ b/R/plot.nlme.mmkin.R
@@ -99,7 +99,7 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
       transform_fractions = fit_1$transform_fractions)
 
     odeini <- degparms_all[ds_i, odeini_names]
-    names(odeini) <- gsub("_0", "", names(odeini))
+    names(odeini) <- gsub("_0", "", odeini_names)
 
     out <- mkinpredict(x$mkinmod, odeparms, odeini,
       outtimes, solution_type = solution_type,
@@ -116,7 +116,7 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
     transform_fractions = fit_1$transform_fractions)
 
   odeini_pop <- degparms_all_pop[odeini_names]
-  names(odeini_pop) <- gsub("_0", "", names(odeini_pop))
+  names(odeini_pop) <- gsub("_0", "", odeini_names)
 
   pred_pop <- as.data.frame(
     mkinpredict(x$mkinmod, odeparms_pop, odeini_pop,
@@ -171,7 +171,6 @@ plot.nlme.mmkin <- function(x, i = 1:ncol(x$mmkin_orig),
       maxabs = max(abs(observed_row$residual), na.rm = TRUE)
     }
 
-
     if (identical(resplot, "time")) {
       plot(0, type = "n", xlim = xlim, xlab = "Time",
         ylim = c(-1.2 * maxabs, 1.2 * maxabs),
diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml
index 61fa6e5d..d6c3d6c9 100644
--- a/docs/dev/pkgdown.yml
+++ b/docs/dev/pkgdown.yml
@@ -10,7 +10,7 @@ articles:
   web_only/NAFTA_examples: NAFTA_examples.html
   web_only/benchmarks: benchmarks.html
   web_only/compiled_models: compiled_models.html
-last_built: 2020-10-23T23:38Z
+last_built: 2020-10-24T00:14Z
 urls:
   reference: https://pkgdown.jrwb.de/mkin/reference
   article: https://pkgdown.jrwb.de/mkin/articles
diff --git a/docs/dev/reference/Rplot001.png b/docs/dev/reference/Rplot001.png
index cfc5bc2b..bf7c274a 100644
--- a/docs/dev/reference/Rplot001.png
+++ b/docs/dev/reference/Rplot001.png
diff --git a/docs/dev/reference/Rplot002.png b/docs/dev/reference/Rplot002.png
index cffa10c1..965d4620 100644
--- a/docs/dev/reference/Rplot002.png
+++ b/docs/dev/reference/Rplot002.png
diff --git a/docs/dev/reference/Rplot003.png b/docs/dev/reference/Rplot003.png
index 89ba6c49..057b525f 100644
--- a/docs/dev/reference/Rplot003.png
+++ b/docs/dev/reference/Rplot003.png
diff --git a/docs/dev/reference/Rplot004.png b/docs/dev/reference/Rplot004.png
index 7d30a181..2b5ba960 100644
--- a/docs/dev/reference/Rplot004.png
+++ b/docs/dev/reference/Rplot004.png
diff --git a/docs/dev/reference/nlme.mmkin-1.png b/docs/dev/reference/nlme.mmkin-1.png
index 564f7e2b..d0a1d7d4 100644
--- a/docs/dev/reference/nlme.mmkin-1.png
+++ b/docs/dev/reference/nlme.mmkin-1.png
diff --git a/docs/dev/reference/nlme.mmkin-2.png b/docs/dev/reference/nlme.mmkin-2.png
index a9ce4636..b68dc3e0 100644
--- a/docs/dev/reference/nlme.mmkin-2.png
+++ b/docs/dev/reference/nlme.mmkin-2.png
diff --git a/docs/dev/reference/nlme.mmkin-3.png b/docs/dev/reference/nlme.mmkin-3.png
index 0b7ce0f6..77804b2c 100644
--- a/docs/dev/reference/nlme.mmkin-3.png
+++ b/docs/dev/reference/nlme.mmkin-3.png
diff --git a/docs/dev/reference/nlme.mmkin-4.png b/docs/dev/reference/nlme.mmkin-4.png
index d7c68dd5..96717087 100644
--- a/docs/dev/reference/nlme.mmkin-4.png
+++ b/docs/dev/reference/nlme.mmkin-4.png
diff --git a/docs/dev/reference/nlme.mmkin.html b/docs/dev/reference/nlme.mmkin.html
index 6e83b700..3c84abe2 100644
--- a/docs/dev/reference/nlme.mmkin.html
+++ b/docs/dev/reference/nlme.mmkin.html
@@ -286,7 +286,8 @@ with additional elements</p>
 #&gt; StdDev: 2.488249 0.8447273 1.32965 0.3289311 2.321364
 #&gt; 
 #&gt; Number of Observations: 90
-#&gt; Number of Groups: 5 </div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop</span><span class='op'>)</span>
+#&gt; Number of Groups: 5 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop</span><span class='op'>)</span>
+</div><div class='img'><img src='nlme.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='endpoints.html'>endpoints</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop</span><span class='op'>)</span>
 </div><div class='output co'>#&gt; $distimes
 #&gt;            DT50     DT90 DT50back  DT50_k1  DT50_k2
 #&gt; parent 10.79857 100.7937 30.34193 4.193938 43.85443
@@ -313,82 +314,24 @@ with additional elements</p>
     A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"min"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
   <span class='va'>m_sfo_sfo_ff</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"A1"</span><span class='op'>)</span>,
     A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, use_of_ff <span class='op'>=</span> <span class='st'>"max"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
-  <span class='va'>m_fomc_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='st'>"A1"</span><span class='op'>)</span>,
-    A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
   <span class='va'>m_dfop_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='st'>"A1"</span><span class='op'>)</span>,
     A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
 
   <span class='va'>f_2</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>m_sfo_sfo</span>,
    <span class='st'>"SFO-SFO-ff"</span> <span class='op'>=</span> <span class='va'>m_sfo_sfo_ff</span>,
-   <span class='st'>"FOMC-SFO"</span> <span class='op'>=</span> <span class='va'>m_fomc_sfo</span>,
    <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>m_dfop_sfo</span><span class='op'>)</span>,
     <span class='va'>ds_2</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
-  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>]</span><span class='op'>)</span> <span class='co'># Separate fits for datasets 3 and 4</span>
-</div><div class='img'><img src='nlme.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'>
+
   <span class='va'>f_nlme_sfo_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
-  <span class='co'># plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures</span>
-  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>)</span> <span class='co'># Global mixed model: Fits for datasets 3 and 4</span>
+  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span>
 </div><div class='img'><img src='nlme.mmkin-2.png' alt='' width='700' height='433' /></div><div class='input'>
   <span class='co'># With formation fractions</span>
   <span class='va'>f_nlme_sfo_sfo_ff</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"SFO-SFO-ff"</span>, <span class='op'>]</span><span class='op'>)</span>
-  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo_ff</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>)</span> <span class='co'># chi2 different due to different df attribution</span>
+  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_sfo_sfo_ff</span><span class='op'>)</span>
 </div><div class='img'><img src='nlme.mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'>
-  <span class='co'># For more parameters, we need to increase pnlsMaxIter and the tolerance</span>
+  <span class='co'># For the following fit we need to increase pnlsMaxIter and the tolerance</span>
   <span class='co'># to get convergence</span>
-  <span class='va'>f_nlme_fomc_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='op'>]</span>,
-    control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>100</span>, tolerance <span class='op'>=</span> <span class='fl'>1e-4</span><span class='op'>)</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; 
-#&gt; **Iteration 1
-#&gt; LME step: Loglik: -394.1603, nlminb iterations: 3
-#&gt; reStruct  parameters:
-#&gt;        ds1        ds2        ds3        ds4        ds5 
-#&gt; -0.2079793  0.8563830  1.7454105  1.0917354  1.2756825 
-#&gt;  Beginning PNLS step: ..  completed fit_nlme() step.
-#&gt; PNLS step: RSS =  643.8803 
-#&gt;  fixed effects: 94.17379  -5.473193  -0.6970236  -0.2025091  2.103883  
-#&gt;  iterations: 100 
-#&gt; Convergence crit. (must all become &lt;= tolerance = 0.0001):
-#&gt;     fixed  reStruct 
-#&gt; 0.7960134 0.1447728 
-#&gt; 
-#&gt; **Iteration 2
-#&gt; LME step: Loglik: -396.3824, nlminb iterations: 7
-#&gt; reStruct  parameters:
-#&gt;           ds1           ds2           ds3           ds4           ds5 
-#&gt; -1.712404e-01 -2.432655e-05  1.842120e+00  1.073975e+00  1.322925e+00 
-#&gt;  Beginning PNLS step: ..  completed fit_nlme() step.
-#&gt; PNLS step: RSS =  643.8035 
-#&gt;  fixed effects: 94.17385  -5.473487  -0.6970404  -0.2025137  2.103871  
-#&gt;  iterations: 100 
-#&gt; Convergence crit. (must all become &lt;= tolerance = 0.0001):
-#&gt;        fixed     reStruct 
-#&gt; 5.382757e-05 1.236667e-03 
-#&gt; 
-#&gt; **Iteration 3
-#&gt; LME step: Loglik: -396.3825, nlminb iterations: 7
-#&gt; reStruct  parameters:
-#&gt;           ds1           ds2           ds3           ds4           ds5 
-#&gt; -0.1712499044 -0.0001499831  1.8420971364  1.0739799123  1.3229167796 
-#&gt;  Beginning PNLS step: ..  completed fit_nlme() step.
-#&gt; PNLS step: RSS =  643.7948 
-#&gt;  fixed effects: 94.17386  -5.473521  -0.6970422  -0.2025144  2.10387  
-#&gt;  iterations: 100 
-#&gt; Convergence crit. (must all become &lt;= tolerance = 0.0001):
-#&gt;        fixed     reStruct 
-#&gt; 6.072817e-06 1.400857e-04 
-#&gt; 
-#&gt; **Iteration 4
-#&gt; LME step: Loglik: -396.3825, nlminb iterations: 7
-#&gt; reStruct  parameters:
-#&gt;           ds1           ds2           ds3           ds4           ds5 
-#&gt; -0.1712529502 -0.0001641277  1.8420957542  1.0739797181  1.3229173076 
-#&gt;  Beginning PNLS step: ..  completed fit_nlme() step.
-#&gt; PNLS step: RSS =  643.7936 
-#&gt;  fixed effects: 94.17386  -5.473526  -0.6970426  -0.2025146  2.103869  
-#&gt;  iterations: 100 
-#&gt; Convergence crit. (must all become &lt;= tolerance = 0.0001):
-#&gt;        fixed     reStruct 
-#&gt; 1.027451e-06 2.275704e-05 </div><div class='input'>  <span class='va'>f_nlme_dfop_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>,
+  <span class='va'>f_nlme_dfop_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span>,
     control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>pnlsMaxIter <span class='op'>=</span> <span class='fl'>120</span>, tolerance <span class='op'>=</span> <span class='fl'>5e-4</span><span class='op'>)</span>, verbose <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
 </div><div class='output co'>#&gt; 
 #&gt; **Iteration 1
@@ -415,17 +358,10 @@ with additional elements</p>
 #&gt;  iterations: 120 
 #&gt; Convergence crit. (must all become &lt;= tolerance = 0.0005):
 #&gt;        fixed     reStruct 
-#&gt; 4.789774e-07 2.200661e-05 </div><div class='input'>  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"FOMC-SFO"</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>]</span><span class='op'>)</span>
-</div><div class='img'><img src='nlme.mmkin-4.png' alt='' width='700' height='433' /></div><div class='input'>  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_fomc_sfo</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>)</span>
-</div><div class='img'><img src='nlme.mmkin-5.png' alt='' width='700' height='433' /></div><div class='input'>
-  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_2</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>]</span><span class='op'>)</span>
-</div><div class='img'><img src='nlme.mmkin-6.png' alt='' width='700' height='433' /></div><div class='input'>  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='fl'>3</span><span class='op'>:</span><span class='fl'>4</span><span class='op'>)</span>
-</div><div class='img'><img src='nlme.mmkin-7.png' alt='' width='700' height='433' /></div><div class='input'>
-  <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_fomc_sfo</span>, <span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span>
-</div><div class='output co'>#&gt;                 Model df       AIC       BIC    logLik   Test   L.Ratio p-value
-#&gt; f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9273                         
-#&gt; f_nlme_fomc_sfo     2 11  818.5149  853.0087 -398.2575 1 vs 2  21.33975  &lt;.0001
-#&gt; f_nlme_sfo_sfo      3  9 1085.1821 1113.4043 -533.5910 2 vs 3 270.66716  &lt;.0001</div><div class='input'>  <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span> <span class='co'># if we ignore FOMC</span>
+#&gt; 4.789774e-07 2.200661e-05 </div><div class='input'>
+  <span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span><span class='op'>)</span>
+</div><div class='img'><img src='nlme.mmkin-4.png' alt='' width='700' height='433' /></div><div class='input'>
+  <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span><span class='op'>(</span><span class='va'>f_nlme_dfop_sfo</span>, <span class='va'>f_nlme_sfo_sfo</span><span class='op'>)</span>
 </div><div class='output co'>#&gt;                 Model df       AIC       BIC    logLik   Test  L.Ratio p-value
 #&gt; f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9273                        
 #&gt; f_nlme_sfo_sfo      2  9 1085.1821 1113.4043 -533.5910 1 vs 2 249.3274  &lt;.0001</div><div class='input'>
@@ -449,19 +385,8 @@ with additional elements</p>
 #&gt; A1     162.30536 539.1667       NA       NA       NA
 #&gt; </div><div class='input'>
   <span class='kw'>if</span> <span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/length.html'>length</a></span><span class='op'>(</span><span class='fu'>findFunction</span><span class='op'>(</span><span class='st'>"varConstProp"</span><span class='op'>)</span><span class='op'>)</span> <span class='op'>&gt;</span> <span class='fl'>0</span><span class='op'>)</span> <span class='op'>{</span> <span class='co'># tc error model for nlme available</span>
-    <span class='co'># Attempts to fit metabolite kinetics with the tc error model</span>
-    <span class='co'>#f_2_tc &lt;- mmkin(list("SFO-SFO" = m_sfo_sfo,</span>
-    <span class='co'>#  "SFO-SFO-ff" = m_sfo_sfo_ff,</span>
-    <span class='co'>#  "FOMC-SFO" = m_fomc_sfo,</span>
-    <span class='co'>#  "DFOP-SFO" = m_dfop_sfo),</span>
-    <span class='co'>#   ds_2, quiet = TRUE,</span>
-    <span class='co'>#   error_model = "tc")</span>
-    <span class='co'>#f_nlme_sfo_sfo_tc &lt;- nlme(f_2_tc["SFO-SFO", ], control = list(maxIter = 100))</span>
-    <span class='co'>#f_nlme_dfop_sfo_tc &lt;- nlme(f_2_tc["DFOP-SFO", ])</span>
-    <span class='co'>#f_nlme_dfop_sfo_tc &lt;- update(f_nlme_dfop_sfo, weights = varConstProp(),</span>
-    <span class='co'>#  control = list(sigma = 1, msMaxIter = 100, pnlsMaxIter = 15))</span>
-    <span class='co'># Fitting metabolite kinetics with nlme.mmkin and the two-component</span>
-    <span class='co'># error model currently does not work, at least not with these data.</span>
+    <span class='co'># Attempts to fit metabolite kinetics with the tc error model are possible,</span>
+    <span class='co'># but need tweeking of control values and sometimes do not converge</span>
 
     <span class='va'>f_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span>
     <span class='va'>f_nlme_sfo_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f_tc</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
diff --git a/man/nlme.mmkin.Rd b/man/nlme.mmkin.Rd
index 08ce1ad8..87d84c74 100644
--- a/man/nlme.mmkin.Rd
+++ b/man/nlme.mmkin.Rd
@@ -83,6 +83,7 @@ f_nlme_sfo <- nlme(f["SFO", ])
 f_nlme_dfop <- nlme(f["DFOP", ])
 AIC(f_nlme_sfo, f_nlme_dfop)
 print(f_nlme_dfop)
+plot(f_nlme_dfop)
 endpoints(f_nlme_dfop)
 \dontrun{
   f_nlme_2 <- nlme(f["SFO", ], start = c(parent_0 = 100, log_k_parent = 0.1))
@@ -93,58 +94,36 @@ endpoints(f_nlme_dfop)
     A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE)
   m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
     A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
-  m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-    A1 = mkinsub("SFO"), quiet = TRUE)
   m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
     A1 = mkinsub("SFO"), quiet = TRUE)
 
   f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo,
    "SFO-SFO-ff" = m_sfo_sfo_ff,
-   "FOMC-SFO" = m_fomc_sfo,
    "DFOP-SFO" = m_dfop_sfo),
     ds_2, quiet = TRUE)
-  plot(f_2["SFO-SFO", 3:4]) # Separate fits for datasets 3 and 4
 
   f_nlme_sfo_sfo <- nlme(f_2["SFO-SFO", ])
-  # plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures
-  plot(f_nlme_sfo_sfo, 3:4) # Global mixed model: Fits for datasets 3 and 4
+  plot(f_nlme_sfo_sfo)
 
   # With formation fractions
   f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
-  plot(f_nlme_sfo_sfo_ff, 3:4) # chi2 different due to different df attribution
+  plot(f_nlme_sfo_sfo_ff)
 
-  # For more parameters, we need to increase pnlsMaxIter and the tolerance
+  # For the following fit we need to increase pnlsMaxIter and the tolerance
   # to get convergence
-  f_nlme_fomc_sfo <- nlme(f_2["FOMC-SFO", ],
-    control = list(pnlsMaxIter = 100, tolerance = 1e-4), verbose = TRUE)
   f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
     control = list(pnlsMaxIter = 120, tolerance = 5e-4), verbose = TRUE)
-  plot(f_2["FOMC-SFO", 3:4])
-  plot(f_nlme_fomc_sfo, 3:4)
 
-  plot(f_2["DFOP-SFO", 3:4])
-  plot(f_nlme_dfop_sfo, 3:4)
+  plot(f_nlme_dfop_sfo)
 
-  anova(f_nlme_dfop_sfo, f_nlme_fomc_sfo, f_nlme_sfo_sfo)
-  anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo) # if we ignore FOMC
+  anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo)
 
   endpoints(f_nlme_sfo_sfo)
   endpoints(f_nlme_dfop_sfo)
 
   if (length(findFunction("varConstProp")) > 0) { # tc error model for nlme available
-    # Attempts to fit metabolite kinetics with the tc error model
-    #f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo,
-    #  "SFO-SFO-ff" = m_sfo_sfo_ff,
-    #  "FOMC-SFO" = m_fomc_sfo,
-    #  "DFOP-SFO" = m_dfop_sfo),
-    #   ds_2, quiet = TRUE,
-    #   error_model = "tc")
-    #f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ], control = list(maxIter = 100))
-    #f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ])
-    #f_nlme_dfop_sfo_tc <- update(f_nlme_dfop_sfo, weights = varConstProp(),
-    #  control = list(sigma = 1, msMaxIter = 100, pnlsMaxIter = 15))
-    # Fitting metabolite kinetics with nlme.mmkin and the two-component
-    # error model currently does not work, at least not with these data.
+    # Attempts to fit metabolite kinetics with the tc error model are possible,
+    # but need tweeking of control values and sometimes do not converge
 
     f_tc <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, error_model = "tc")
     f_nlme_sfo_tc <- nlme(f_tc["SFO", ])