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authorJohannes Ranke <jranke@uni-bremen.de>2020-11-06 00:03:29 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2020-11-06 00:03:29 +0100
commitb5b446b718b15ccaae5b197e147fc1358f0f564e (patch)
treea36f32ee664c6925b5afdb812daca41075968152 /docs/dev/reference/saemix.html
parent2f24fe0ce70d040e491619d7f2413fc902e433f1 (diff)
Fast analytical solutions for saemix, update.mmkin
Also, use logit transformation for g and for solitary formation fractions, addressing #10.
Diffstat (limited to 'docs/dev/reference/saemix.html')
-rw-r--r--docs/dev/reference/saemix.html974
1 files changed, 748 insertions, 226 deletions
diff --git a/docs/dev/reference/saemix.html b/docs/dev/reference/saemix.html
index c8cf9fab..5dacefc9 100644
--- a/docs/dev/reference/saemix.html
+++ b/docs/dev/reference/saemix.html
@@ -190,16 +190,15 @@ mmkin. Starting variances of the random effects (argument omega.init) are the
variances of the deviations of the parameters from these mean values.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
- <pre class="examples"><div class='input'><span class='va'>ds</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span>,
- <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>$</span><span class='va'>data</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'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span><span class='op'>)</span>
-<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Dataset"</span>, <span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>)</span>
-<span class='va'>sfo_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'>"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><span class='op'>)</span>
-</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='co'># \dontrun{</span>
-<span class='va'>f_mmkin</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'>sfo_sfo</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
+ <pre class="examples"><div class='input'><span class='co'># \dontrun{</span>
<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'>saemix</span><span class='op'>)</span>
</div><div class='output co'>#&gt; <span class='message'>Package saemix, version 3.1.9000</span>
-#&gt; <span class='message'> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='input'><span class='va'>m_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
+#&gt; <span class='message'> please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='input'><span class='va'>ds</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span>,
+ <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>$</span><span class='va'>data</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'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span><span class='op'>)</span>
+<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Dataset"</span>, <span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>)</span>
+<span class='va'>f_mmkin_parent_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>ds</span>, cores <span class='op'>=</span> <span class='fl'>1</span>,
+ state.ini <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>100</span><span class='op'>)</span>, fixed_initials <span class='op'>=</span> <span class='st'>"parent"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
+<span class='va'>m_saemix_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_parent_p0_fixed</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixModel object was successfully created:
@@ -208,59 +207,236 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; Model function: Mixed model generated from mmkin object Model type: structural
#&gt; function (psi, id, xidep)
#&gt; {
-#&gt; uid &lt;- unique(id)
-#&gt; res_list &lt;- parallel::mclapply(uid, function(i) {
-#&gt; transparms_optim &lt;- psi[i, ]
-#&gt; names(transparms_optim) &lt;- names(degparms_optim)
-#&gt; odeini_optim &lt;- transparms_optim[odeini_optim_parm_names]
-#&gt; names(odeini_optim) &lt;- gsub("_0$", "", odeini_optim_parm_names)
-#&gt; odeini &lt;- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
-#&gt; ode_transparms_optim_names &lt;- setdiff(names(transparms_optim),
-#&gt; odeini_optim_parm_names)
-#&gt; odeparms_optim &lt;- backtransform_odeparms(transparms_optim[ode_transparms_optim_names],
-#&gt; mkin_model, transform_rates = object[[1]]$transform_rates,
-#&gt; transform_fractions = object[[1]]$transform_fractions)
-#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
-#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
-#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
-#&gt; odeparms)
-#&gt; }
-#&gt; else {
-#&gt; i_time &lt;- xidep_i$time
-#&gt; i_name &lt;- xidep_i$name
-#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
-#&gt; outtimes = sort(unique(i_time)))
-#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
-#&gt; out_values &lt;- out_wide[out_index]
-#&gt; }
-#&gt; return(out_values)
-#&gt; }, mc.cores = cores)
-#&gt; res &lt;- unlist(res_list)
-#&gt; return(res)
+#&gt; odeini_fixed/(xidep[, "time"]/exp(psi[id, 2]) + 1)^exp(psi[id,
+#&gt; 1])
+#&gt; }
+#&gt; &lt;bytecode: 0x5555599945b8&gt;
+#&gt; &lt;environment: 0x555559984388&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] log_alpha normal Estimated
+#&gt; [2,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; log_alpha log_beta
+#&gt; log_alpha 1 0
+#&gt; log_beta 0 1
+#&gt; Error model: constant , initial values: a.1=2.95893806804889
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; log_alpha log_beta
+#&gt; Pop.CondInit -0.347996 1.66788</div><div class='input'><span class='va'>d_saemix_parent</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin_parent_p0_fixed</span><span class='op'>)</span>
+</div><div class='output co'>#&gt;
+#&gt;
+#&gt; The following SaemixData object was successfully created:
+#&gt;
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>saemix_options</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>seed <span class='op'>=</span> <span class='fl'>123456</span>, displayProgress <span class='op'>=</span> <span class='cn'>FALSE</span>,
+ save <span class='op'>=</span> <span class='cn'>FALSE</span>, save.graphs <span class='op'>=</span> <span class='cn'>FALSE</span>, nbiter.saemix <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='fl'>200</span>, <span class='fl'>80</span><span class='op'>)</span><span class='op'>)</span>
+<span class='va'>f_saemix_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_p0_fixed</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:29 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:30 2020"</div><div class='img'><img src='saemix-1.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; odeini_fixed/(xidep[, "time"]/exp(psi[id, 2]) + 1)^exp(psi[id,
+#&gt; 1])
+#&gt; }
+#&gt; &lt;bytecode: 0x5555599945b8&gt;
+#&gt; &lt;environment: 0x555559984388&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] log_alpha normal Estimated
+#&gt; [2,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; log_alpha log_beta
+#&gt; log_alpha 1 0
+#&gt; log_beta 0 1
+#&gt; Error model: constant , initial values: a.1=2.95893806804889
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; log_alpha log_beta
+#&gt; Pop.CondInit -0.347996 1.66788
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; log_alpha -0.33 0.30 91.6
+#&gt; log_beta 1.70 0.21 12.4
+#&gt; a a.1 3.15 0.25 7.9
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; log_alpha omega2.log_alpha 0.44 0.28 65
+#&gt; log_beta omega2.log_beta 0.18 0.14 79
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.log_alpha omega2.log_beta
+#&gt; omega2.log_alpha 1 0
+#&gt; omega2.log_beta 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 501.6082
+#&gt; AIC = 511.6082
+#&gt; BIC = 509.6554
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 501.7
+#&gt; AIC = 511.7
+#&gt; BIC = 509.7472
+#&gt; ----------------------------------------------------</div><div class='input'>
+<span class='va'>f_mmkin_parent</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'>"FOMC"</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><span class='op'>)</span>
+<span class='va'>m_saemix_sfo</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
+</div><div class='output co'>#&gt;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1] * exp(-exp(psi[id, 2]) * xidep[, "time"])
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555e35c170&gt;
+#&gt; &lt;bytecode: 0x55555998d588&gt;
+#&gt; &lt;environment: 0x55555c0f4ae8&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: parent_0 log_k_parent
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_parent normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_k_parent
+#&gt; parent_0 1 0
+#&gt; log_k_parent 0 1
+#&gt; Error model: constant , initial values: a.1=5.76827561471585
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_k_parent
+#&gt; Pop.CondInit 86.39406 -3.215063</div><div class='input'><span class='va'>m_saemix_fomc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
+</div><div class='output co'>#&gt;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x5555595d7668&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.91976382242696
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 94.43884 -0.2226095 2.048192</div><div class='input'><span class='va'>m_saemix_dfop</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"DFOP"</span>, <span class='op'>]</span><span class='op'>)</span>
+</div><div class='output co'>#&gt;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; g &lt;- plogis(psi[id, 4])
+#&gt; t = xidep[, "time"]
+#&gt; psi[id, 1] * (g * exp(-exp(psi[id, 2]) * t) + (1 - g) * exp(-exp(psi[id,
+#&gt; 3]) * t))
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998e548&gt;
+#&gt; &lt;environment: 0x555558225bf0&gt;
#&gt; Nb of parameters: 4
-#&gt; parameter names: parent_0 log_k_parent log_k_A1 f_parent_ilr_1
+#&gt; parameter names: parent_0 log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
-#&gt; [3,] log_k_A1 normal Estimated
-#&gt; [4,] f_parent_ilr_1 normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k1 normal Estimated
+#&gt; [3,] log_k2 normal Estimated
+#&gt; [4,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; parent_0 1 0 0 0
-#&gt; log_k_parent 0 1 0 0
-#&gt; log_k_A1 0 0 1 0
-#&gt; f_parent_ilr_1 0 0 0 1
-#&gt; Error model: constant , initial values: a.1=4.97259024646577
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0
+#&gt; log_k1 0 1 0 0
+#&gt; log_k2 0 0 1 0
+#&gt; g_qlogis 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.94671278396371
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; Pop.CondInit 86.53449 -3.207005 -3.060308 -1.920449</div><div class='input'><span class='va'>d_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span>
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 94.08322 -1.834163 -4.210797 0.11002</div><div class='input'><span class='va'>d_saemix_parent</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixData object was successfully created:
@@ -269,15 +445,12 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; longitudinal data for use with the SAEM algorithm
#&gt; Dataset ds_saemix
#&gt; Structured data: value ~ time + name | ds
-#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>saemix_options</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>seed <span class='op'>=</span> <span class='fl'>123456</span>,
- save <span class='op'>=</span> <span class='cn'>FALSE</span>, save.graphs <span class='op'>=</span> <span class='cn'>FALSE</span>, displayProgress <span class='op'>=</span> <span class='cn'>FALSE</span>,
- nbiter.saemix <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='fl'>200</span>, <span class='fl'>80</span><span class='op'>)</span><span class='op'>)</span>
-<span class='va'>f_saemix</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix</span>, <span class='va'>d_saemix</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>f_saemix_sfo</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_sfo</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Thu Nov 5 08:26:39 2020"
+#&gt; [1] "Thu Nov 5 23:53:31 2020"
#&gt; ..
#&gt; Minimisation finished
-#&gt; [1] "Thu Nov 5 08:28:33 2020"</div><div class='img'><img src='saemix-1.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:32 2020"</div><div class='img'><img src='saemix-2.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
#&gt; -----------------------------------
#&gt; ---- Data ----
#&gt; -----------------------------------
@@ -288,8 +461,8 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; X variable for graphs: time ()
#&gt; Dataset characteristics:
#&gt; number of subjects: 5
-#&gt; number of observations: 170
-#&gt; average/min/max nb obs: 34.00 / 30 / 38
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
#&gt; First 10 lines of data:
#&gt; ds time name value mdv cens occ ytype
#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
@@ -309,59 +482,248 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; Model function: Mixed model generated from mmkin object Model type: structural
#&gt; function (psi, id, xidep)
#&gt; {
-#&gt; uid &lt;- unique(id)
-#&gt; res_list &lt;- parallel::mclapply(uid, function(i) {
-#&gt; transparms_optim &lt;- psi[i, ]
-#&gt; names(transparms_optim) &lt;- names(degparms_optim)
-#&gt; odeini_optim &lt;- transparms_optim[odeini_optim_parm_names]
-#&gt; names(odeini_optim) &lt;- gsub("_0$", "", odeini_optim_parm_names)
-#&gt; odeini &lt;- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
-#&gt; ode_transparms_optim_names &lt;- setdiff(names(transparms_optim),
-#&gt; odeini_optim_parm_names)
-#&gt; odeparms_optim &lt;- backtransform_odeparms(transparms_optim[ode_transparms_optim_names],
-#&gt; mkin_model, transform_rates = object[[1]]$transform_rates,
-#&gt; transform_fractions = object[[1]]$transform_fractions)
-#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
-#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
-#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
-#&gt; odeparms)
-#&gt; }
-#&gt; else {
-#&gt; i_time &lt;- xidep_i$time
-#&gt; i_name &lt;- xidep_i$name
-#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
-#&gt; outtimes = sort(unique(i_time)))
-#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
-#&gt; out_values &lt;- out_wide[out_index]
-#&gt; }
-#&gt; return(out_values)
-#&gt; }, mc.cores = cores)
-#&gt; res &lt;- unlist(res_list)
-#&gt; return(res)
+#&gt; psi[id, 1] * exp(-exp(psi[id, 2]) * xidep[, "time"])
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555e35c170&gt;
+#&gt; &lt;bytecode: 0x55555998d588&gt;
+#&gt; &lt;environment: 0x55555c0f4ae8&gt;
+#&gt; Nb of parameters: 2
+#&gt; parameter names: parent_0 log_k_parent
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_parent normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_k_parent
+#&gt; parent_0 1 0
+#&gt; log_k_parent 0 1
+#&gt; Error model: constant , initial values: a.1=5.76827561471585
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_k_parent
+#&gt; Pop.CondInit 86.39406 -3.215063
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 85.8 1.85 2.2
+#&gt; log_k_parent -3.2 0.59 18.3
+#&gt; a a.1 6.2 0.49 7.9
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 7.8 10.7 138
+#&gt; log_k_parent omega2.log_k_parent 1.7 1.1 64
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.parent_0 omega2.log_k_parent
+#&gt; omega2.parent_0 1 0
+#&gt; omega2.log_k_parent 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 615.4074
+#&gt; AIC = 625.4074
+#&gt; BIC = 623.4546
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 614.4911
+#&gt; AIC = 624.4911
+#&gt; BIC = 622.5382
+#&gt; ----------------------------------------------------</div><div class='input'><span class='va'>f_saemix_fomc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_fomc</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:33 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:34 2020"</div><div class='img'><img src='saemix-3.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x5555595d7668&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.91976382242696
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 94.43884 -0.2226095 2.048192
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 94.49 1.18 1.2
+#&gt; log_alpha -0.21 0.30 142.0
+#&gt; log_beta 2.06 0.21 10.4
+#&gt; a a.1 2.28 0.19 8.2
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 4.66 4.34 93
+#&gt; log_alpha omega2.log_alpha 0.45 0.29 65
+#&gt; log_beta omega2.log_beta 0.19 0.14 75
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.parent_0 omega2.log_alpha omega2.log_beta
+#&gt; omega2.parent_0 1 0 0
+#&gt; omega2.log_alpha 0 1 0
+#&gt; omega2.log_beta 0 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 454.0598
+#&gt; AIC = 468.0598
+#&gt; BIC = 465.3259
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 453.7499
+#&gt; AIC = 467.7499
+#&gt; BIC = 465.016
+#&gt; ----------------------------------------------------</div><div class='input'><span class='va'>f_saemix_dfop</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_dfop</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:35 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:37 2020"</div><div class='img'><img src='saemix-4.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; g &lt;- plogis(psi[id, 4])
+#&gt; t = xidep[, "time"]
+#&gt; psi[id, 1] * (g * exp(-exp(psi[id, 2]) * t) + (1 - g) * exp(-exp(psi[id,
+#&gt; 3]) * t))
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998e548&gt;
+#&gt; &lt;environment: 0x555558225bf0&gt;
#&gt; Nb of parameters: 4
-#&gt; parameter names: parent_0 log_k_parent log_k_A1 f_parent_ilr_1
+#&gt; parameter names: parent_0 log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
-#&gt; [3,] log_k_A1 normal Estimated
-#&gt; [4,] f_parent_ilr_1 normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k1 normal Estimated
+#&gt; [3,] log_k2 normal Estimated
+#&gt; [4,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; parent_0 1 0 0 0
-#&gt; log_k_parent 0 1 0 0
-#&gt; log_k_A1 0 0 1 0
-#&gt; f_parent_ilr_1 0 0 0 1
-#&gt; Error model: constant , initial values: a.1=4.97259024646577
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0
+#&gt; log_k1 0 1 0 0
+#&gt; log_k2 0 0 1 0
+#&gt; g_qlogis 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.94671278396371
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent log_k_A1 f_parent_ilr_1
-#&gt; Pop.CondInit 86.53449 -3.207005 -3.060308 -1.920449
+#&gt; parent_0 log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 94.08322 -1.834163 -4.210797 0.11002
#&gt; -----------------------------------
#&gt; ---- Key algorithm options ----
#&gt; -----------------------------------
@@ -383,69 +745,195 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; ----------------------------------------------------
#&gt; ----------------- Fixed effects ------------------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 86.09 1.57 1.8
-#&gt; log_k_parent -3.21 0.59 18.5
-#&gt; log_k_A1 -4.69 0.31 6.6
-#&gt; f_parent_ilr_1 -0.34 0.30 89.2
-#&gt; a a.1 4.69 0.27 5.8
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 93.97 1.35 1.4
+#&gt; log_k1 -2.37 0.58 24.5
+#&gt; log_k2 -3.63 0.87 24.0
+#&gt; g_qlogis -0.14 0.34 246.1
+#&gt; a a.1 2.32 0.19 8.3
#&gt; ----------------------------------------------------
#&gt; ----------- Variance of random effects -----------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 omega2.parent_0 7.07 7.72 109
-#&gt; log_k_parent omega2.log_k_parent 1.75 1.11 63
-#&gt; log_k_A1 omega2.log_k_A1 0.28 0.28 99
-#&gt; f_parent_ilr_1 omega2.f_parent_ilr_1 0.39 0.27 71
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 6.97 5.72 82
+#&gt; log_k1 omega2.log_k1 1.63 1.06 65
+#&gt; log_k2 omega2.log_k2 3.73 2.39 64
+#&gt; g_qlogis omega2.g_qlogis 0.16 0.27 173
#&gt; ----------------------------------------------------
#&gt; ------ Correlation matrix of random effects ------
#&gt; ----------------------------------------------------
-#&gt; omega2.parent_0 omega2.log_k_parent omega2.log_k_A1
-#&gt; omega2.parent_0 1 0 0
-#&gt; omega2.log_k_parent 0 1 0
-#&gt; omega2.log_k_A1 0 0 1
-#&gt; omega2.f_parent_ilr_1 0 0 0
-#&gt; omega2.f_parent_ilr_1
-#&gt; omega2.parent_0 0
-#&gt; omega2.log_k_parent 0
-#&gt; omega2.log_k_A1 0
-#&gt; omega2.f_parent_ilr_1 1
+#&gt; omega2.parent_0 omega2.log_k1 omega2.log_k2 omega2.g_qlogis
+#&gt; omega2.parent_0 1 0 0 0
+#&gt; omega2.log_k1 0 1 0 0
+#&gt; omega2.log_k2 0 0 1 0
+#&gt; omega2.g_qlogis 0 0 0 1
#&gt; ----------------------------------------------------
#&gt; --------------- Statistical criteria -------------
#&gt; ----------------------------------------------------
#&gt; Likelihood computed by linearisation
-#&gt; -2LL= 1064.35
-#&gt; AIC = 1082.35
-#&gt; BIC = 1078.835
+#&gt; -2LL= 485.4627
+#&gt; AIC = 503.4627
+#&gt; BIC = 499.9477
#&gt;
#&gt; Likelihood computed by importance sampling
-#&gt; -2LL= 1063.475
-#&gt; AIC = 1081.475
-#&gt; BIC = 1077.96
-#&gt; ----------------------------------------------------</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saemix</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span>
-</div><div class='output co'>#&gt; Plotting convergence plots</div><div class='img'><img src='saemix-2.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span>
-<span class='co'># Synthetic data with two-component error</span>
-<span class='va'>sampling_times</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='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='op'>)</span>
-<span class='va'>dt50_sfo_in</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>80</span>, <span class='fl'>90</span>, <span class='fl'>100</span>, <span class='fl'>111.111</span>, <span class='fl'>125</span><span class='op'>)</span>
-<span class='va'>k_in</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/Log.html'>log</a></span><span class='op'>(</span><span class='fl'>2</span><span class='op'>)</span> <span class='op'>/</span> <span class='va'>dt50_sfo_in</span>
-
-<span class='va'>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'>"SFO"</span><span class='op'>)</span><span class='op'>)</span>
-
-<span class='va'>pred_sfo</span> <span class='op'>&lt;-</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>k</span><span class='op'>)</span> <span class='op'>{</span>
- <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k_parent <span class='op'>=</span> <span class='va'>k</span><span class='op'>)</span>,
- <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>100</span><span class='op'>)</span>, <span class='va'>sampling_times</span><span class='op'>)</span>
-<span class='op'>}</span>
-
-<span class='va'>ds_sfo_mean</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>k_in</span>, <span class='va'>pred_sfo</span><span class='op'>)</span>
-<span class='fu'><a href='https://rdrr.io/r/base/Random.html'>set.seed</a></span><span class='op'>(</span><span class='fl'>123456L</span><span class='op'>)</span>
-<span class='va'>ds_sfo_syn</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>ds_sfo_mean</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'>{</span>
- <span class='fu'><a href='add_err.html'>add_err</a></span><span class='op'>(</span><span class='va'>ds</span>, sdfunc <span class='op'>=</span> <span class='kw'>function</span><span class='op'>(</span><span class='va'>value</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>sqrt</a></span><span class='op'>(</span><span class='fl'>1</span><span class='op'>^</span><span class='fl'>2</span> <span class='op'>+</span> <span class='va'>value</span><span class='op'>^</span><span class='fl'>2</span> <span class='op'>*</span> <span class='fl'>0.07</span><span class='op'>^</span><span class='fl'>2</span><span class='op'>)</span>,
- n <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span><span class='op'>[[</span><span class='fl'>1</span><span class='op'>]</span><span class='op'>]</span>
- <span class='op'>}</span><span class='op'>)</span>
-<span class='co'># \dontrun{</span>
-<span class='va'>f_mmkin_syn</span> <span class='op'>&lt;-</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_syn</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
-<span class='co'># plot(f_mmkin_syn)</span>
-<span class='va'>m_saemix_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_syn</span>, cores <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
+#&gt; -2LL= 473.563
+#&gt; AIC = 491.563
+#&gt; BIC = 488.048
+#&gt; ----------------------------------------------------</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</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='va'>f_saemix_sfo</span>, <span class='va'>f_saemix_fomc</span>, <span class='va'>f_saemix_dfop</span><span class='op'>)</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Likelihoods computed by importance sampling </div><div class='output co'>#&gt; AIC BIC
+#&gt; 1 624.4911 622.5382
+#&gt; 2 467.7499 465.0160
+#&gt; 3 491.5630 488.0480</div><div class='input'><span class='va'>f_mmkin_parent_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span>
+<span class='va'>m_saemix_fomc_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin_parent_tc</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
+</div><div class='output co'>#&gt;
+#&gt;
+#&gt; The following SaemixModel object was successfully created:
+#&gt;
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x555559a957f8&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: combined , initial values: a.1=1.10728182011691 b.1=0.024889924291374
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 93.13042 -0.1215336 2.230815</div><div class='input'><span class='va'>f_saemix_fomc_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_fomc_tc</span>, <span class='va'>d_saemix_parent</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Running main SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:53:38 2020"
+#&gt; ..
+#&gt; Minimisation finished
+#&gt; [1] "Thu Nov 5 23:53:42 2020"</div><div class='img'><img src='saemix-5.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; -----------------------------------
+#&gt; ---- Data ----
+#&gt; -----------------------------------
+#&gt; Object of class SaemixData
+#&gt; longitudinal data for use with the SAEM algorithm
+#&gt; Dataset ds_saemix
+#&gt; Structured data: value ~ time + name | ds
+#&gt; X variable for graphs: time ()
+#&gt; Dataset characteristics:
+#&gt; number of subjects: 5
+#&gt; number of observations: 90
+#&gt; average/min/max nb obs: 18.00 / 16 / 20
+#&gt; First 10 lines of data:
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
+#&gt; -----------------------------------
+#&gt; ---- Model ----
+#&gt; -----------------------------------
+#&gt; Nonlinear mixed-effects model
+#&gt; Model function: Mixed model generated from mmkin object Model type: structural
+#&gt; function (psi, id, xidep)
+#&gt; {
+#&gt; psi[id, 1]/(xidep[, "time"]/exp(psi[id, 3]) + 1)^exp(psi[id,
+#&gt; 2])
+#&gt; }
+#&gt; &lt;bytecode: 0x55555998dc50&gt;
+#&gt; &lt;environment: 0x555559a957f8&gt;
+#&gt; Nb of parameters: 3
+#&gt; parameter names: parent_0 log_alpha log_beta
+#&gt; distribution:
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_alpha normal Estimated
+#&gt; [3,] log_beta normal Estimated
+#&gt; Variance-covariance matrix:
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 1 0 0
+#&gt; log_alpha 0 1 0
+#&gt; log_beta 0 0 1
+#&gt; Error model: combined , initial values: a.1=1.10728182011691 b.1=0.024889924291374
+#&gt; No covariate in the model.
+#&gt; Initial values
+#&gt; parent_0 log_alpha log_beta
+#&gt; Pop.CondInit 93.13042 -0.1215336 2.230815
+#&gt; -----------------------------------
+#&gt; ---- Key algorithm options ----
+#&gt; -----------------------------------
+#&gt; Estimation of individual parameters (MAP)
+#&gt; Estimation of standard errors and linearised log-likelihood
+#&gt; Estimation of log-likelihood by importance sampling
+#&gt; Number of iterations: K1=200, K2=80
+#&gt; Number of chains: 10
+#&gt; Seed: 123456
+#&gt; Number of MCMC iterations for IS: 5000
+#&gt; Simulations:
+#&gt; nb of simulated datasets used for npde: 1000
+#&gt; nb of simulated datasets used for VPC: 100
+#&gt; Input/output
+#&gt; save the results to a file: FALSE
+#&gt; save the graphs to files: FALSE
+#&gt; ----------------------------------------------------
+#&gt; ---- Results ----
+#&gt; ----------------------------------------------------
+#&gt; ----------------- Fixed effects ------------------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 94.4481 1.2052 1.3
+#&gt; log_alpha -0.2088 0.3059 146.5
+#&gt; log_beta 2.0668 0.2182 10.6
+#&gt; a a.1 2.4273 0.3178 13.1
+#&gt; b b.1 -0.0037 0.0062 168.3
+#&gt; ----------------------------------------------------
+#&gt; ----------- Variance of random effects -----------
+#&gt; ----------------------------------------------------
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 5.34 4.58 86
+#&gt; log_alpha omega2.log_alpha 0.46 0.29 65
+#&gt; log_beta omega2.log_beta 0.20 0.15 74
+#&gt; ----------------------------------------------------
+#&gt; ------ Correlation matrix of random effects ------
+#&gt; ----------------------------------------------------
+#&gt; omega2.parent_0 omega2.log_alpha omega2.log_beta
+#&gt; omega2.parent_0 1 0 0
+#&gt; omega2.log_alpha 0 1 0
+#&gt; omega2.log_beta 0 0 1
+#&gt; ----------------------------------------------------
+#&gt; --------------- Statistical criteria -------------
+#&gt; ----------------------------------------------------
+#&gt; Likelihood computed by linearisation
+#&gt; -2LL= 453.7703
+#&gt; AIC = 469.7703
+#&gt; BIC = 466.6458
+#&gt;
+#&gt; Likelihood computed by importance sampling
+#&gt; -2LL= 453.6186
+#&gt; AIC = 469.6186
+#&gt; BIC = 466.4942
+#&gt; ----------------------------------------------------</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</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='va'>f_saemix_fomc</span>, <span class='va'>f_saemix_fomc_tc</span><span class='op'>)</span><span class='op'>)</span>
+</div><div class='output co'>#&gt; Likelihoods computed by importance sampling </div><div class='output co'>#&gt; AIC BIC
+#&gt; 1 467.7499 465.0160
+#&gt; 2 469.6186 466.4942</div><div class='input'>
+<span class='va'>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><span class='op'>)</span>
+</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='va'>f_mmkin</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'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>dfop_sfo</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
+<span class='va'>m_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixModel object was successfully created:
@@ -468,7 +956,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; transform_fractions = object[[1]]$transform_fractions)
#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
+#&gt; if (solution_type == "analytical") {
#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
#&gt; odeparms)
#&gt; }
@@ -476,7 +964,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; i_time &lt;- xidep_i$time
#&gt; i_name &lt;- xidep_i$name
#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
+#&gt; odeini = odeini, solution_type = solution_type,
#&gt; outtimes = sort(unique(i_time)))
#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
#&gt; out_values &lt;- out_wide[out_index]
@@ -486,23 +974,31 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; res &lt;- unlist(res_list)
#&gt; return(res)
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555cd8e028&gt;
-#&gt; Nb of parameters: 2
-#&gt; parameter names: parent_0 log_k_parent
+#&gt; &lt;bytecode: 0x55555998cba0&gt;
+#&gt; &lt;environment: 0x55555bd1fee8&gt;
+#&gt; Nb of parameters: 6
+#&gt; parameter names: parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_A1 normal Estimated
+#&gt; [3,] f_parent_qlogis normal Estimated
+#&gt; [4,] log_k1 normal Estimated
+#&gt; [5,] log_k2 normal Estimated
+#&gt; [6,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent
-#&gt; parent_0 1 0
-#&gt; log_k_parent 0 1
-#&gt; Error model: combined , initial values: a.1=1.05209877924905 b.1=0.0586479225303944
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0 0 0
+#&gt; log_k_A1 0 1 0 0 0 0
+#&gt; f_parent_qlogis 0 0 1 0 0 0
+#&gt; log_k1 0 0 0 1 0 0
+#&gt; log_k2 0 0 0 0 1 0
+#&gt; g_qlogis 0 0 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.64723790168612
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent
-#&gt; Pop.CondInit 100.315 -4.962075</div><div class='input'><span class='va'>d_saemix_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin_syn</span><span class='op'>)</span>
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 93.81015 -9.764746 -0.9711148 -1.879937 -4.270814 0.1356441</div><div class='input'><span class='va'>d_saemix</span> <span class='op'>&lt;-</span> <span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>)</span>
</div><div class='output co'>#&gt;
#&gt;
#&gt; The following SaemixData object was successfully created:
@@ -511,12 +1007,12 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; longitudinal data for use with the SAEM algorithm
#&gt; Dataset ds_saemix
#&gt; Structured data: value ~ time + name | ds
-#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>f_saemix_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix_tc</span>, <span class='va'>d_saemix_tc</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
+#&gt; X variable for graphs: time () </div><div class='input'><span class='va'>f_saemix</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix</a></span><span class='op'>(</span><span class='va'>m_saemix</span>, <span class='va'>d_saemix</span>, <span class='va'>saemix_options</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
-#&gt; [1] "Thu Nov 5 08:28:50 2020"
+#&gt; [1] "Thu Nov 5 23:53:43 2020"
#&gt; ..
#&gt; Minimisation finished
-#&gt; [1] "Thu Nov 5 08:29:41 2020"</div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
+#&gt; [1] "Thu Nov 5 23:56:33 2020"</div><div class='img'><img src='saemix-6.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by the SAEM algorithm
#&gt; -----------------------------------
#&gt; ---- Data ----
#&gt; -----------------------------------
@@ -527,20 +1023,20 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; X variable for graphs: time ()
#&gt; Dataset characteristics:
#&gt; number of subjects: 5
-#&gt; number of observations: 90
-#&gt; average/min/max nb obs: 18.00 / 18 / 18
+#&gt; number of observations: 170
+#&gt; average/min/max nb obs: 34.00 / 30 / 38
#&gt; First 10 lines of data:
-#&gt; ds time name value mdv cens occ ytype
-#&gt; 1 1 0 parent 105.9 0 0 1 1
-#&gt; 2 1 0 parent 98.0 0 0 1 1
-#&gt; 3 1 1 parent 96.6 0 0 1 1
-#&gt; 4 1 1 parent 99.8 0 0 1 1
-#&gt; 5 1 3 parent 113.0 0 0 1 1
-#&gt; 6 1 3 parent 103.2 0 0 1 1
-#&gt; 7 1 7 parent 102.9 0 0 1 1
-#&gt; 8 1 7 parent 110.8 0 0 1 1
-#&gt; 9 1 14 parent 95.9 0 0 1 1
-#&gt; 10 1 14 parent 85.9 0 0 1 1
+#&gt; ds time name value mdv cens occ ytype
+#&gt; 1 Dataset 6 0 parent 97.2 0 0 1 1
+#&gt; 2 Dataset 6 0 parent 96.4 0 0 1 1
+#&gt; 3 Dataset 6 3 parent 71.1 0 0 1 1
+#&gt; 4 Dataset 6 3 parent 69.2 0 0 1 1
+#&gt; 5 Dataset 6 6 parent 58.1 0 0 1 1
+#&gt; 6 Dataset 6 6 parent 56.6 0 0 1 1
+#&gt; 7 Dataset 6 10 parent 44.4 0 0 1 1
+#&gt; 8 Dataset 6 10 parent 43.4 0 0 1 1
+#&gt; 9 Dataset 6 20 parent 33.3 0 0 1 1
+#&gt; 10 Dataset 6 20 parent 29.2 0 0 1 1
#&gt; -----------------------------------
#&gt; ---- Model ----
#&gt; -----------------------------------
@@ -562,7 +1058,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; transform_fractions = object[[1]]$transform_fractions)
#&gt; odeparms &lt;- c(odeparms_optim, odeparms_fixed)
#&gt; xidep_i &lt;- subset(xidep, id == i)
-#&gt; if (analytical) {
+#&gt; if (solution_type == "analytical") {
#&gt; out_values &lt;- mkin_model$deg_func(xidep_i, odeini,
#&gt; odeparms)
#&gt; }
@@ -570,7 +1066,7 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; i_time &lt;- xidep_i$time
#&gt; i_name &lt;- xidep_i$name
#&gt; out_wide &lt;- mkinpredict(mkin_model, odeparms = odeparms,
-#&gt; odeini = odeini, solution_type = object[[1]]$solution_type,
+#&gt; odeini = odeini, solution_type = solution_type,
#&gt; outtimes = sort(unique(i_time)))
#&gt; out_index &lt;- cbind(as.character(i_time), as.character(i_name))
#&gt; out_values &lt;- out_wide[out_index]
@@ -580,23 +1076,31 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; res &lt;- unlist(res_list)
#&gt; return(res)
#&gt; }
-#&gt; &lt;bytecode: 0x55555d62aeb8&gt;
-#&gt; &lt;environment: 0x55555cd8e028&gt;
-#&gt; Nb of parameters: 2
-#&gt; parameter names: parent_0 log_k_parent
+#&gt; &lt;bytecode: 0x55555998cba0&gt;
+#&gt; &lt;environment: 0x55555bd1fee8&gt;
+#&gt; Nb of parameters: 6
+#&gt; parameter names: parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
#&gt; distribution:
-#&gt; Parameter Distribution Estimated
-#&gt; [1,] parent_0 normal Estimated
-#&gt; [2,] log_k_parent normal Estimated
+#&gt; Parameter Distribution Estimated
+#&gt; [1,] parent_0 normal Estimated
+#&gt; [2,] log_k_A1 normal Estimated
+#&gt; [3,] f_parent_qlogis normal Estimated
+#&gt; [4,] log_k1 normal Estimated
+#&gt; [5,] log_k2 normal Estimated
+#&gt; [6,] g_qlogis normal Estimated
#&gt; Variance-covariance matrix:
-#&gt; parent_0 log_k_parent
-#&gt; parent_0 1 0
-#&gt; log_k_parent 0 1
-#&gt; Error model: combined , initial values: a.1=1.05209877924905 b.1=0.0586479225303944
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; parent_0 1 0 0 0 0 0
+#&gt; log_k_A1 0 1 0 0 0 0
+#&gt; f_parent_qlogis 0 0 1 0 0 0
+#&gt; log_k1 0 0 0 1 0 0
+#&gt; log_k2 0 0 0 0 1 0
+#&gt; g_qlogis 0 0 0 0 0 1
+#&gt; Error model: constant , initial values: a.1=1.64723790168612
#&gt; No covariate in the model.
#&gt; Initial values
-#&gt; parent_0 log_k_parent
-#&gt; Pop.CondInit 100.315 -4.962075
+#&gt; parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
+#&gt; Pop.CondInit 93.81015 -9.764746 -0.9711148 -1.879937 -4.270814 0.1356441
#&gt; -----------------------------------
#&gt; ---- Key algorithm options ----
#&gt; -----------------------------------
@@ -618,37 +1122,55 @@ variances of the deviations of the parameters from these mean values.</p>
#&gt; ----------------------------------------------------
#&gt; ----------------- Fixed effects ------------------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 100.232 1.266 1.3
-#&gt; log_k_parent -4.961 0.089 1.8
-#&gt; a a.1 -0.106 1.211 1142.0
-#&gt; b b.1 0.071 0.017 24.2
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 93.78 1.35 1.4
+#&gt; log_k_A1 -6.05 1.12 18.5
+#&gt; f_parent_qlogis -0.97 0.20 21.1
+#&gt; log_k1 -2.46 0.51 20.7
+#&gt; log_k2 -3.63 0.95 26.3
+#&gt; g_qlogis -0.08 0.36 447.7
+#&gt; a a.1 1.88 0.11 5.9
#&gt; ----------------------------------------------------
#&gt; ----------- Variance of random effects -----------
#&gt; ----------------------------------------------------
-#&gt; Parameter Estimate SE CV(%)
-#&gt; parent_0 omega2.parent_0 3.334 5.024 151
-#&gt; log_k_parent omega2.log_k_parent 0.036 0.024 68
+#&gt; Parameter Estimate SE CV(%)
+#&gt; parent_0 omega2.parent_0 7.85 5.76 73
+#&gt; log_k_A1 omega2.log_k_A1 4.27 3.44 80
+#&gt; f_parent_qlogis omega2.f_parent_qlogis 0.20 0.13 65
+#&gt; log_k1 omega2.log_k1 1.08 0.77 72
+#&gt; log_k2 omega2.log_k2 4.24 2.83 67
+#&gt; g_qlogis omega2.g_qlogis 0.21 0.26 123
#&gt; ----------------------------------------------------
#&gt; ------ Correlation matrix of random effects ------
#&gt; ----------------------------------------------------
-#&gt; omega2.parent_0 omega2.log_k_parent
-#&gt; omega2.parent_0 1 0
-#&gt; omega2.log_k_parent 0 1
+#&gt; omega2.parent_0 omega2.log_k_A1 omega2.f_parent_qlogis
+#&gt; omega2.parent_0 1 0 0
+#&gt; omega2.log_k_A1 0 1 0
+#&gt; omega2.f_parent_qlogis 0 0 1
+#&gt; omega2.log_k1 0 0 0
+#&gt; omega2.log_k2 0 0 0
+#&gt; omega2.g_qlogis 0 0 0
+#&gt; omega2.log_k1 omega2.log_k2 omega2.g_qlogis
+#&gt; omega2.parent_0 0 0 0
+#&gt; omega2.log_k_A1 0 0 0
+#&gt; omega2.f_parent_qlogis 0 0 0
+#&gt; omega2.log_k1 1 0 0
+#&gt; omega2.log_k2 0 1 0
+#&gt; omega2.g_qlogis 0 0 1
#&gt; ----------------------------------------------------
#&gt; --------------- Statistical criteria -------------
#&gt; ----------------------------------------------------
#&gt; Likelihood computed by linearisation
-#&gt; -2LL= 575.5586
-#&gt; AIC = 587.5586
-#&gt; BIC = 585.2153
+#&gt; -2LL= 879.7721
+#&gt; AIC = 905.7721
+#&gt; BIC = 900.6948
#&gt;
#&gt; Likelihood computed by importance sampling
-#&gt; -2LL= 575.7797
-#&gt; AIC = 587.7797
-#&gt; BIC = 585.4364
-#&gt; ----------------------------------------------------</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saemix_tc</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span>
-</div><div class='img'><img src='saemix-3.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Plotting convergence plots</div><div class='img'><img src='saemix-4.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># }</span>
+#&gt; -2LL= 816.8276
+#&gt; AIC = 842.8276
+#&gt; BIC = 837.7503
+#&gt; ----------------------------------------------------</div><div class='input'>
+<span class='co'># }</span>
</div></pre>
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