Merge branch 'master' into nlmixr

After the merge, run make test and accept the new snapshot for the mixed
model fit for an nlme object

1 files changed, 24 insertions, 9 deletions

diff --git a/man/dimethenamid_2018.Rd b/man/dimethenamid_2018.Rd
index 93fcad26..a0e5bbea 100644
--- a/man/dimethenamid_2018.Rd
+++ b/man/dimethenamid_2018.Rd
@@ -11,7 +11,7 @@ An \link{mkindsg} object grouping eight datasets with some meta information
 Rapporteur Member State Germany, Co-Rapporteur Member State Bulgaria (2018)
 Renewal Assessment Report Dimethenamid-P Volume 3 - B.8 Environmental fate and behaviour
 Rev. 2 - November 2017
-\url{http://registerofquestions.efsa.europa.eu/roqFrontend/outputLoader?output=ON-5211}
+\url{https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716}
 }
 \usage{
 dimethenamid_2018
@@ -56,16 +56,31 @@ f_dmta_mkin_tc <- mmkin(
   list("DFOP-SFO3+" = dfop_sfo3_plus),
   dmta_ds, quiet = TRUE, error_model = "tc")
 nlmixr_model(f_dmta_mkin_tc)
-f_dmta_nlmixr_focei <- nlmixr(f_dmta_mkin_tc, est = "focei",
-  control = nlmixr::foceiControl(print = 500))
+# The focei fit takes about four minutes on my system
+system.time(
+  f_dmta_nlmixr_focei <- nlmixr(f_dmta_mkin_tc, est = "focei",
+    control = nlmixr::foceiControl(print = 500))
+)
 summary(f_dmta_nlmixr_focei)
 plot(f_dmta_nlmixr_focei)
-# saem has a problem with this model/data combination, maybe because of the
-# overparameterised error model, to be investigated
-#f_dmta_nlmixr_saem <- nlmixr(f_dmta_mkin_tc, est = "saem",
-#  control = saemControl(print = 500))
-#summary(f_dmta_nlmixr_saem)
-#plot(f_dmta_nlmixr_saem)
+# Using saemix takes about 18 minutes
+system.time(
+  f_dmta_saemix <- saem(f_dmta_mkin_tc, test_log_parms = TRUE)
+)
+
+# nlmixr with est = "saem" is pretty fast with default iteration numbers, most
+# of the time (about 2.5 minutes) is spent for calculating the log likelihood at the end
+# The likelihood calculated for the nlmixr fit is much lower than that found by saemix
+# Also, the trace plot and the plot of the individual predictions is not
+# convincing for the parent. It seems we are fitting an overparameterised
+# model, so the result we get strongly depends on starting parameters and control settings.
+system.time(
+  f_dmta_nlmixr_saem <- nlmixr(f_dmta_mkin_tc, est = "saem",
+    control = nlmixr::saemControl(print = 500, logLik = TRUE, nmc = 9))
+)
+traceplot(f_dmta_nlmixr_saem$nm)
+summary(f_dmta_nlmixr_saem)
+plot(f_dmta_nlmixr_saem)
 }
 }
 \keyword{datasets}