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, 0 insertions, 66 deletions

diff --git a/vignettes/web_only/dimethenamid_2018.R b/vignettes/web_only/dimethenamid_2018.R
deleted file mode 100644
index 625cceb8..00000000
--- a/vignettes/web_only/dimethenamid_2018.R
+++ /dev/null
@@ -1,66 +0,0 @@
-## ---- include = FALSE---------------------------------------------------------
-require(knitr)
-options(digits = 5)
-opts_chunk$set(
-  comment = "",
-  tidy = FALSE,
-  cache = TRUE
-)
-
-## ----dimethenamid_data--------------------------------------------------------
-library(mkin)
-dmta_ds <- lapply(1:8, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
-  ds_i
-})
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-dmta_ds[["Borstel"]] <- rbind(dmta_ds[["Borstel 1"]], dmta_ds[["Borstel 2"]])
-dmta_ds[["Borstel 1"]] <- NULL
-dmta_ds[["Borstel 2"]] <- NULL
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
-
-## ----f_parent_mkin------------------------------------------------------------
-f_parent_mkin_const <- mmkin(c("SFO", "DFOP"), dmta_ds,
-  error_model = "const", quiet = TRUE)
-f_parent_mkin_tc <- mmkin(c("SFO", "DFOP"), dmta_ds,
-  error_model = "tc", quiet = TRUE)
-
-## ----f_parent_mkin_sfo_const--------------------------------------------------
-plot(mixed(f_parent_mkin_const["SFO", ]))
-
-## ----f_parent_mkin_dfop_const-------------------------------------------------
-plot(mixed(f_parent_mkin_const["DFOP", ]))
-
-## ----f_parent_mkin_dfop_const_test--------------------------------------------
-plot(mixed(f_parent_mkin_const["DFOP", ]), test_log_parms = TRUE)
-
-## ----f_parent_mkin_dfop_tc_test-----------------------------------------------
-plot(mixed(f_parent_mkin_tc["DFOP", ]), test_log_parms = TRUE)
-
-## ----f_parent_nlme, warning = FALSE-------------------------------------------
-f_parent_nlme_sfo_const <- nlme(f_parent_mkin_const["SFO", ])
-#f_parent_nlme_dfop_const <- nlme(f_parent_mkin_const["DFOP", ]) # error
-f_parent_nlme_sfo_tc <- nlme(f_parent_mkin_tc["SFO", ])
-f_parent_nlme_dfop_tc <- nlme(f_parent_mkin_tc["DFOP", ])
-
-## ----f_parent_nlme_logchol, warning = FALSE, eval = FALSE---------------------
-#  f_parent_nlme_sfo_const_logchol <- nlme(f_parent_mkin_const["SFO", ],
-#    random = pdLogChol(list(DMTA_0 ~ 1, log_k_DMTA ~ 1)))
-#  anova(f_parent_nlme_sfo_const, f_parent_nlme_sfo_const_logchol) # not better
-#  f_parent_nlme_dfop_tc_logchol <- update(f_parent_nlme_dfop_tc,
-#    random = pdLogChol(list(DMTA_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1)))
-#  # using log Cholesky parameterisation for random effects (nlme default) does
-#  # not converge and gives lots of warnings about the LME step not converging
-
-## ----AIC_parent_nlme----------------------------------------------------------
-anova(
-  f_parent_nlme_sfo_const, f_parent_nlme_sfo_tc, f_parent_nlme_dfop_tc
-)
-
-## ----plot_parent_nlme---------------------------------------------------------
-plot(f_parent_nlme_dfop_tc)
-