Add three functions to facilitate the use of nlme

11 files changed, 368 insertions, 508 deletions

diff --git a/NAMESPACE b/NAMESPACE
index b16541ca..1b53f101 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -45,7 +45,7 @@ export(max_twa_fomc)
 export(max_twa_hs)
 export(max_twa_parent)
 export(max_twa_sfo)
-export(memkin)
+export(mean_degparms)
 export(mkin_long_to_wide)
 export(mkin_wide_to_long)
 export(mkinds)
@@ -60,6 +60,8 @@ export(mkinresplot)
 export(mkinsub)
 export(mmkin)
 export(nafta)
+export(nlme_data)
+export(nlme_function)
 export(parms)
 export(plot_err)
 export(plot_res)
diff --git a/NEWS.md b/NEWS.md
index a2258e77..46d2d711 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -1,5 +1,7 @@
 # mkin 0.9.49.10 (unreleased)
 
+- 'mean_degparms, nlme_data, nlme_function': Three new functions to facilitate building nlme models from mmkin row objects
+
 - 'endpoints': Don't return the SFORB list component if it's empty. This reduces distraction and complies with the documentation
 
 - Article in compiled models: Add some platform specific code and suppress warnings about zero values being removed from the FOCUS D dataset
diff --git a/R/memkin.R b/R/memkin.R
deleted file mode 100644
index 8a71484e..00000000
--- a/R/memkin.R
+++ /dev/null
@@ -1,170 +0,0 @@
-#' Estimation of parameter distributions from mmkin row objects
-#'
-#' This function sets up and attempts to fit a mixed effects model to
-#' an mmkin row object which is essentially a list of mkinfit objects
-#' that have been obtained by fitting the same model to a list of
-#' datasets.
-#'
-#' @param object An mmkin row object containing several fits of the same model to different datasets
-#' @param random_spec Either "auto" or a specification of random effects for \code{\link{nlme}}
-#'   given as a character vector
-#' @param ... Additional arguments passed to \code{\link{nlme}}
-#' @import nlme
-#' @importFrom purrr map_dfr
-#' @return An nlme object
-#' @examples
-#' sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-#' m_SFO <- mkinmod(parent = mkinsub("SFO"))
-#' d_SFO_1 <- mkinpredict(m_SFO,
-#'   c(k_parent_sink = 0.1),
-#'   c(parent = 98), sampling_times)
-#' d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
-#' d_SFO_2 <- mkinpredict(m_SFO,
-#'   c(k_parent_sink = 0.05),
-#'   c(parent = 102), sampling_times)
-#' d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
-#' d_SFO_3 <- mkinpredict(m_SFO,
-#'   c(k_parent_sink = 0.02),
-#'   c(parent = 103), sampling_times)
-#' d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
-#'
-#' d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
-#' d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
-#' d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
-#' ds <- c(d1 = d1, d2 = d2, d3 = d3)
-#'
-#' f <- mmkin("SFO", ds)
-#' x <- memkin(f)
-#' summary(x)
-#'
-#' ds_2 <- lapply(experimental_data_for_UBA_2019[6:10],
-#'  function(x) x$data[c("name", "time", "value")])
-#' m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
-#'   A1 = mkinsub("SFO"), use_of_ff = "min")
-#' m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
-#'   A1 = mkinsub("SFO"), use_of_ff = "max")
-#' m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-#'   A1 = mkinsub("SFO"))
-#' m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-#'   A1 = mkinsub("SFO"))
-#' m_sforb_sfo <- mkinmod(parent = mkinsub("SFORB", "A1"),
-#'   A1 = mkinsub("SFO"))
-#'
-#' f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo,
-#'  "SFO-SFO-ff" = m_sfo_sfo_ff,
-#'  "FOMC-SFO" = m_fomc_sfo,
-#'  "DFOP-SFO" = m_dfop_sfo,
-#'  "SFORB-SFO" = m_sforb_sfo),
-#'   ds_2)
-#'
-#' f_nlme_sfo_sfo <- memkin(f_2[1, ])
-#' f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit
-#' f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced
-#' f_nlme_sfo_sfo_4 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink ~ 1)") # further reduced
-#' \dontrun{
-#'   f_nlme_sfo_sfo_ff <- memkin(f_2[2, ]) # does not converge with maxIter = 50
-#' }
-#' f_nlme_fomc_sfo <- memkin(f_2[3, ])
-#' \dontrun{
-#'   f_nlme_dfop_sfo <- memkin(f_2[4, ])  # apparently underdetermined
-#'   f_nlme_sforb_sfo <- memkin(f_2[5, ]) # also does not converge
-#' }
-#' anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo, f_nlme_sfo_sfo_4)
-#' @export
-memkin <- function(object, random_spec = "auto", ...) {
-  if (nrow(object) > 1) stop("Only row objects allowed")
-  ds_names <- colnames(object)
-
-  p_mat_start_trans <- sapply(object, parms, transformed = TRUE)
-  colnames(p_mat_start_trans) <- ds_names
-
-  p_names_mean_function <- setdiff(rownames(p_mat_start_trans), names(object[[1]]$errparms))
-  p_start_mean_function <- apply(p_mat_start_trans[p_names_mean_function, ], 1, mean)
-
-  ds_list <- lapply(object, function(x) x$data[c("time", "variable", "observed")])
-  names(ds_list) <- ds_names
-  ds_nlme <- purrr::map_dfr(ds_list, function(x) x, .id = "ds")
-  ds_nlme$variable <- as.character(ds_nlme$variable)
-  ds_nlme_grouped <- groupedData(observed ~ time | ds, ds_nlme)
-
-  mkin_model <- object[[1]]$mkinmod
-
-  # Inspired by https://stackoverflow.com/a/12983961/3805440
-  # and https://stackoverflow.com/a/26280789/3805440
-  model_function_alist <- replicate(length(p_names_mean_function) + 2, substitute())
-  names(model_function_alist) <- c("name", "time", p_names_mean_function)
-
-  model_function_body <- quote({
-    arg_frame <- as.data.frame(as.list((environment())), stringsAsFactors = FALSE)
-    res_frame <- arg_frame[1:2]
-    parm_frame <- arg_frame[-(1:2)]
-    parms_unique <- unique(parm_frame)
-
-    n_unique <- nrow(parms_unique)
-
-    times_ds <- list()
-    names_ds <- list()
-    for (i in 1:n_unique) {
-      times_ds[[i]] <-
-        arg_frame[which(arg_frame[[3]] == parms_unique[i, 1]), "time"]
-      names_ds[[i]] <-
-        arg_frame[which(arg_frame[[3]] == parms_unique[i, 1]), "name"]
-    }
-
-    res_list <- lapply(1:n_unique, function(x) {
-      transparms_optim <- unlist(parms_unique[x, , drop = TRUE])
-      parms_fixed <- object[[1]]$bparms.fixed
-
-      odeini_optim_parm_names <- grep('_0$', names(transparms_optim), value = TRUE)
-      odeini_optim <- transparms_optim[odeini_optim_parm_names]
-      names(odeini_optim) <- gsub('_0$', '', odeini_optim_parm_names)
-      odeini_fixed_parm_names <- grep('_0$', names(parms_fixed), value = TRUE)
-      odeini_fixed <- parms_fixed[odeini_fixed_parm_names]
-      names(odeini_fixed) <- gsub('_0$', '', odeini_fixed_parm_names)
-      odeini <- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
-
-      ode_transparms_optim_names <- setdiff(names(transparms_optim), odeini_optim_parm_names)
-      odeparms_optim <- backtransform_odeparms(transparms_optim[ode_transparms_optim_names], mkin_model,
-        transform_rates = object[[1]]$transform_rates,
-        transform_fractions = object[[1]]$transform_fractions)
-      odeparms_fixed_names <- setdiff(names(parms_fixed), odeini_fixed_parm_names)
-      odeparms_fixed <- parms_fixed[odeparms_fixed_names]
-      odeparms <- c(odeparms_optim, odeparms_fixed)
-
-      out_wide <- mkinpredict(mkin_model,
-        odeparms = odeparms, odeini = odeini,
-        solution_type = object[[1]]$solution_type,
-        outtimes = sort(unique(times_ds[[x]])))
-      out_array <- out_wide[, -1, drop = FALSE]
-      rownames(out_array) <- as.character(unique(times_ds[[x]]))
-      out_times <- as.character(times_ds[[x]])
-      out_names <- as.character(names_ds[[x]])
-      out_values <- mapply(function(times, names) out_array[times, names],
-        out_times, out_names)
-      return(as.numeric(out_values))
-    })
-    res <- unlist(res_list)
-    return(res)
-  })
-  model_function <- as.function(c(model_function_alist, model_function_body))
-  # For some reason, using envir = parent.frame() here is not enough,
-  # we need to use assign
-  assign("model_function", model_function, envir = parent.frame())
-
-  random_spec <- if (random_spec[1] == "auto") {
-      paste0("pdDiag(", paste(p_names_mean_function, collapse = " + "), " ~ 1),\n")
-  } else {
-      paste0(random_spec, ",\n")
-  }
-  nlme_call_text <- paste0(
-    "nlme(observed ~ model_function(variable, time, ",
-      paste(p_names_mean_function, collapse = ", "), "),\n",
-    "  data = ds_nlme_grouped,\n",
-    "  fixed = ", paste(p_names_mean_function, collapse = " + "), " ~ 1,\n",
-    "  random = ", random_spec, "\n",
-    "  start = p_start_mean_function)\n")
-
-  f_nlme <- eval(parse(text = nlme_call_text))
-
-  return(f_nlme)
-}
diff --git a/R/mkinsub.R b/R/mkinsub.R
index db91ca00..f87c230a 100644
--- a/R/mkinsub.R
+++ b/R/mkinsub.R
@@ -27,11 +27,12 @@
 #'   parent = mkinsub("SFO", "m1"),
 #'   m1 = mkinsub("SFO"))
 #' 
-#' # Now supplying full names
-#' SFO_SFO.2 <- mkinmod(
-#'   parent = mkinsub("SFO", "m1", full_name = "Test compound"),
-#'   m1 = mkinsub("SFO", full_name = "Metabolite M1"))
-#' 
+#' \dontrun{
+#'   # Now supplying full names
+#'   SFO_SFO.2 <- mkinmod(
+#'     parent = mkinsub("SFO", "m1", full_name = "Test compound"),
+#'     m1 = mkinsub("SFO", full_name = "Metabolite M1"))
+#'  }
 #' @export
 mkinsub <- function(submodel, to = NULL, sink = TRUE, full_name = NA)
 {
diff --git a/R/nlme.R b/R/nlme.R
new file mode 100644
index 00000000..b17fe15a
--- /dev/null
+++ b/R/nlme.R
@@ -0,0 +1,213 @@
+#' Estimation of parameter distributions from mmkin row objects
+#'
+#' This function sets up and attempts to fit a mixed effects model to
+#' an mmkin row object. An mmkin row object is essentially a list of mkinfit
+#' objects that have been obtained by fitting the same model to a list of
+#' datasets.
+#'
+#' @param object An mmkin row object containing several fits of the same model to different datasets
+#' @import nlme
+#' @importFrom purrr map_dfr
+#' @return A named vector containing mean values of the fitted degradation model parameters
+#' @rdname nlme
+#' @examples
+#' sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+#' m_SFO <- mkinmod(parent = mkinsub("SFO"))
+#' d_SFO_1 <- mkinpredict(m_SFO,
+#'   c(k_parent_sink = 0.1),
+#'   c(parent = 98), sampling_times)
+#' d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
+#' d_SFO_2 <- mkinpredict(m_SFO,
+#'   c(k_parent_sink = 0.05),
+#'   c(parent = 102), sampling_times)
+#' d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
+#' d_SFO_3 <- mkinpredict(m_SFO,
+#'   c(k_parent_sink = 0.02),
+#'   c(parent = 103), sampling_times)
+#' d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
+#'
+#' d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
+#' d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
+#' d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
+#' ds <- c(d1 = d1, d2 = d2, d3 = d3)
+#'
+#' f <- mmkin("SFO", ds, cores = 1, quiet = TRUE)
+#' mean_dp <- mean_degparms(f)
+#' grouped_data <- nlme_data(f)
+#' nlme_f <- nlme_function(f)
+#'
+#' library(nlme)
+#' m_nlme <- nlme(value ~ nlme_f(name, time, parent_0, log_k_parent_sink),
+#'   data = grouped_data,
+#'   fixed = parent_0 + log_k_parent_sink ~ 1,
+#'   random = pdDiag(parent_0 + log_k_parent_sink ~ 1),
+#'   start = mean_dp)
+#' summary(m_nlme)
+#'
+#' \dontrun{
+#'   Test on some real data
+#'   ds_2 <- lapply(experimental_data_for_UBA_2019[6:10],
+#'    function(x) x$data[c("name", "time", "value")])
+#'   m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
+#'     A1 = mkinsub("SFO"), use_of_ff = "min")
+#'   m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
+#'     A1 = mkinsub("SFO"), use_of_ff = "max")
+#'   m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
+#'     A1 = mkinsub("SFO"))
+#'   m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
+#'     A1 = mkinsub("SFO"))
+#'   m_sforb_sfo <- mkinmod(parent = mkinsub("SFORB", "A1"),
+#'     A1 = mkinsub("SFO"))
+#'
+#'   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,
+#'    "SFORB-SFO" = m_sforb_sfo),
+#'     ds_2)
+#'
+#'   grouped_data_2 <- nlme_data(f_2["SFO-SFO", ])
+#'
+#'   mean_dp_sfo_sfo <- mean_degparms(f_2["SFO-SFO", ])
+#'   mean_dp_sfo_sfo_ff <- mean_degparms(f_2["SFO-SFO-ff", ])
+#'   mean_dp_fomc_sfo <- mean_degparms(f_2["FOMC-SFO", ])
+#'   mean_dp_dfop_sfo <- mean_degparms(f_2["DFOP-SFO", ])
+#'   mean_dp_sforb_sfo <- mean_degparms(f_2["SFORB-SFO", ])
+#'
+#'   nlme_f_sfo_sfo <- nlme_function(f_2["SFO-SFO", ])
+#'   nlme_f_sfo_sfo_ff <- nlme_function(f_2["SFO-SFO-ff", ])
+#'   nlme_f_fomc_sfo <- nlme_function(f_2["FOMC-SFO", ])
+#'
+#'   # Allowing for correlations between random effects leads to non-convergence
+#'   f_nlme_sfo_sfo <- nlme(value ~ nlme_f_sfo_sfo(name, time,
+#'        parent_0, log_k_parent_sink, log_k_parent_A1, log_k_A1_sink),
+#'      data = grouped_data_2,
+#'      fixed = parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1,
+#'      random = pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1),
+#'      start = mean_dp_sfo_sfo)
+#'
+#'   # The same model fitted with transformed formation fractions does not converge
+#'   f_nlme_sfo_sfo_ff <- nlme(value ~ nlme_f_sfo_sfo_ff(name, time,
+#'        parent_0, log_k_parent, log_k_A1, f_parent_ilr_1),
+#'      data = grouped_data_2,
+#'      fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1,
+#'      random = pdDiag(parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1),
+#'      start = mean_dp_sfo_sfo_ff)
+#'
+#'   # It does converge with this version of reduced random effects
+#'   f_nlme_sfo_sfo_ff <- nlme(value ~ nlme_f_sfo_sfo_ff(name, time,
+#'        parent_0, log_k_parent, log_k_A1, f_parent_ilr_1),
+#'      data = grouped_data_2,
+#'      fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1,
+#'      random = pdDiag(parent_0 + log_k_parent ~ 1),
+#'      start = mean_dp_sfo_sfo_ff)
+#'
+#'   f_nlme_fomc_sfo <- nlme(value ~ nlme_f_fomc_sfo(name, time,
+#'        parent_0, log_alpha, log_beta, log_k_A1, f_parent_ilr_1),
+#'      data = grouped_data_2,
+#'      fixed = parent_0 + log_alpha + log_beta + log_k_A1 + f_parent_ilr_1 ~ 1,
+#'      random = pdDiag(parent_0 + log_alpha + log_beta + log_k_A1 + f_parent_ilr_1 ~ 1),
+#'      start = mean_dp_fomc_sfo)
+#'
+#'   # DFOP-SFO and SFORB-SFO did not converge with full random effects
+#'
+#'   anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo)
+#' }
+#' @export
+mean_degparms <- function(object) {
+  if (nrow(object) > 1) stop("Only row objects allowed")
+  p_mat_start_trans <- sapply(object, parms, transformed = TRUE)
+  mean_degparm_names <- setdiff(rownames(p_mat_start_trans), names(object[[1]]$errparms))
+  res <- apply(p_mat_start_trans[mean_degparm_names, ], 1, mean)
+  return(res)
+}
+
+#' @rdname nlme
+#' @importFrom purrr map_dfr
+#' @return A groupedData data object
+#' @export
+nlme_data <- function(object) {
+  if (nrow(object) > 1) stop("Only row objects allowed")
+  ds_names <- colnames(object)
+
+  ds_list <- lapply(object, function(x) x$data[c("time", "variable", "observed")])
+  names(ds_list) <- ds_names
+  ds_nlme <- purrr::map_dfr(ds_list, function(x) x, .id = "ds")
+  ds_nlme$variable <- as.character(ds_nlme$variable)
+  ds_nlme_renamed <- data.frame(ds = ds_nlme$ds, name = ds_nlme$variable,
+    time = ds_nlme$time, value = ds_nlme$observed,
+    stringsAsFactors = FALSE)
+  ds_nlme_grouped <- groupedData(value ~ time | ds, ds_nlme_renamed)
+  return(ds_nlme_grouped)
+}
+
+#' @rdname nlme
+#' @return A function that can be used with nlme
+#' @export
+nlme_function <- function(object) {
+  if (nrow(object) > 1) stop("Only row objects allowed")
+
+  mkin_model <- object[[1]]$mkinmod
+
+  degparm_names <- names(mean_degparms(object))
+
+  # Inspired by https://stackoverflow.com/a/12983961/3805440
+  # and https://stackoverflow.com/a/26280789/3805440
+  model_function_alist <- replicate(length(degparm_names) + 2, substitute())
+  names(model_function_alist) <- c("name", "time", degparm_names)
+
+  model_function_body <- quote({
+    arg_frame <- as.data.frame(as.list((environment())), stringsAsFactors = FALSE)
+    res_frame <- arg_frame[1:2]
+    parm_frame <- arg_frame[-(1:2)]
+    parms_unique <- unique(parm_frame)
+
+    n_unique <- nrow(parms_unique)
+
+    times_ds <- list()
+    names_ds <- list()
+    for (i in 1:n_unique) {
+      times_ds[[i]] <-
+        arg_frame[which(arg_frame[[3]] == parms_unique[i, 1]), "time"]
+      names_ds[[i]] <-
+        arg_frame[which(arg_frame[[3]] == parms_unique[i, 1]), "name"]
+    }
+
+    res_list <- lapply(1:n_unique, function(x) {
+      transparms_optim <- unlist(parms_unique[x, , drop = TRUE])
+      parms_fixed <- object[[1]]$bparms.fixed
+
+      odeini_optim_parm_names <- grep('_0$', names(transparms_optim), value = TRUE)
+      odeini_optim <- transparms_optim[odeini_optim_parm_names]
+      names(odeini_optim) <- gsub('_0$', '', odeini_optim_parm_names)
+      odeini_fixed_parm_names <- grep('_0$', names(parms_fixed), value = TRUE)
+      odeini_fixed <- parms_fixed[odeini_fixed_parm_names]
+      names(odeini_fixed) <- gsub('_0$', '', odeini_fixed_parm_names)
+      odeini <- c(odeini_optim, odeini_fixed)[names(mkin_model$diffs)]
+
+      ode_transparms_optim_names <- setdiff(names(transparms_optim), odeini_optim_parm_names)
+      odeparms_optim <- backtransform_odeparms(transparms_optim[ode_transparms_optim_names], mkin_model,
+        transform_rates = object[[1]]$transform_rates,
+        transform_fractions = object[[1]]$transform_fractions)
+      odeparms_fixed_names <- setdiff(names(parms_fixed), odeini_fixed_parm_names)
+      odeparms_fixed <- parms_fixed[odeparms_fixed_names]
+      odeparms <- c(odeparms_optim, odeparms_fixed)
+
+      out_wide <- mkinpredict(mkin_model,
+        odeparms = odeparms, odeini = odeini,
+        solution_type = object[[1]]$solution_type,
+        outtimes = sort(unique(times_ds[[x]])))
+      out_array <- out_wide[, -1, drop = FALSE]
+      rownames(out_array) <- as.character(unique(times_ds[[x]]))
+      out_times <- as.character(times_ds[[x]])
+      out_names <- as.character(names_ds[[x]])
+      out_values <- mapply(function(times, names) out_array[times, names],
+        out_times, out_names)
+      return(as.numeric(out_values))
+    })
+    res <- unlist(res_list)
+    return(res)
+  })
+  model_function <- as.function(c(model_function_alist, model_function_body))
+  return(model_function)
+}
diff --git a/check.log b/check.log
index 3bf43d07..0a75a713 100644
--- a/check.log
+++ b/check.log
@@ -24,27 +24,7 @@ Maintainer: ‘Johannes Ranke <jranke@uni-bremen.de>’
 * checking for future file timestamps ... OK
 * checking ‘build’ directory ... OK
 * checking DESCRIPTION meta-information ... OK
-* checking top-level files ... WARNING
-Conversion of ‘README.md’ failed:
-[WARNING] This document format requires a nonempty <title> element.
-  Please specify either ‘title’ or ‘pagetitle’ in the metadata.
-  Falling back to ‘README’
-Could not fetch https://codecov.io/github/jranke/mkin/branch/master/graphs/badge.svg
-HttpExceptionRequest Request {
-  host                 = "codecov.io"
-  port                 = 443
-  secure               = True
-  requestHeaders       = []
-  path                 = "/github/jranke/mkin/branch/master/graphs/badge.svg"
-  queryString          = ""
-  method               = "GET"
-  proxy                = Nothing
-  rawBody              = False
-  redirectCount        = 10
-  responseTimeout      = ResponseTimeoutDefault
-  requestVersion       = HTTP/1.1
-}
- ConnectionTimeout
+* checking top-level files ... OK
 * checking for left-over files ... OK
 * checking index information ... OK
 * checking package subdirectories ... OK
@@ -64,13 +44,7 @@ HttpExceptionRequest Request {
 * checking R code for possible problems ... OK
 * checking Rd files ... OK
 * checking Rd metadata ... OK
-* checking Rd line widths ... NOTE
-Rd file 'memkin.Rd':
-  \examples lines wider than 100 characters:
-     f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit
-     f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced
-
-These lines will be truncated in the PDF manual.
+* checking Rd line widths ... OK
 * checking Rd cross-references ... OK
 * checking for missing documentation entries ... OK
 * checking for code/documentation mismatches ... OK
@@ -82,41 +56,7 @@ These lines will be truncated in the PDF manual.
 * checking data for ASCII and uncompressed saves ... OK
 * checking installed files from ‘inst/doc’ ... OK
 * checking files in ‘vignettes’ ... OK
-* checking examples ... ERROR
-Running examples in ‘mkin-Ex.R’ failed
-The error most likely occurred in:
-
-> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
-> ### Name: memkin
-> ### Title: Estimation of parameter distributions from mmkin row objects
-> ### Aliases: memkin
-> 
-> ### ** Examples
-> 
-> sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-> m_SFO <- mkinmod(parent = mkinsub("SFO"))
-> d_SFO_1 <- mkinpredict(m_SFO,
-+   c(k_parent_sink = 0.1),
-+   c(parent = 98), sampling_times)
-> d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
-> d_SFO_2 <- mkinpredict(m_SFO,
-+   c(k_parent_sink = 0.05),
-+   c(parent = 102), sampling_times)
-> d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
-> d_SFO_3 <- mkinpredict(m_SFO,
-+   c(k_parent_sink = 0.02),
-+   c(parent = 103), sampling_times)
-> d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
-> 
-> d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
-> d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
-> d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
-> ds <- c(d1 = d1, d2 = d2, d3 = d3)
-> 
-> f <- mmkin("SFO", ds)
-Error in .check_ncores(cores) : 8 simultaneous processes spawned
-Calls: mmkin -> mclapply -> .check_ncores
-Execution halted
+* checking examples ... OK
 * checking for unstated dependencies in ‘tests’ ... OK
 * checking tests ... SKIPPED
 * checking for unstated dependencies in vignettes ... OK
@@ -126,8 +66,5 @@ Execution halted
 * checking for detritus in the temp directory ... OK
 * DONE
 
-Status: 1 ERROR, 1 WARNING, 1 NOTE
-See
-  ‘/home/jranke/git/mkin/mkin.Rcheck/00check.log’
-for details.
+Status: OK
 
diff --git a/man/memkin.Rd b/man/memkin.Rd
deleted file mode 100644
index 8ae6100a..00000000
--- a/man/memkin.Rd
+++ /dev/null
@@ -1,84 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/memkin.R
-\name{memkin}
-\alias{memkin}
-\title{Estimation of parameter distributions from mmkin row objects}
-\usage{
-memkin(object, random_spec = "auto", ...)
-}
-\arguments{
-\item{object}{An mmkin row object containing several fits of the same model to different datasets}
-
-\item{random_spec}{Either "auto" or a specification of random effects for \code{\link{nlme}}
-given as a character vector}
-
-\item{...}{Additional arguments passed to \code{\link{nlme}}}
-}
-\value{
-An nlme object
-}
-\description{
-This function sets up and attempts to fit a mixed effects model to
-an mmkin row object which is essentially a list of mkinfit objects
-that have been obtained by fitting the same model to a list of
-datasets.
-}
-\examples{
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-m_SFO <- mkinmod(parent = mkinsub("SFO"))
-d_SFO_1 <- mkinpredict(m_SFO,
-  c(k_parent_sink = 0.1),
-  c(parent = 98), sampling_times)
-d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
-d_SFO_2 <- mkinpredict(m_SFO,
-  c(k_parent_sink = 0.05),
-  c(parent = 102), sampling_times)
-d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
-d_SFO_3 <- mkinpredict(m_SFO,
-  c(k_parent_sink = 0.02),
-  c(parent = 103), sampling_times)
-d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
-
-d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
-d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
-d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
-ds <- c(d1 = d1, d2 = d2, d3 = d3)
-
-f <- mmkin("SFO", ds)
-x <- memkin(f)
-summary(x)
-
-ds_2 <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) x$data[c("name", "time", "value")])
-m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
-  A1 = mkinsub("SFO"), use_of_ff = "min")
-m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
-  A1 = mkinsub("SFO"), use_of_ff = "max")
-m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-  A1 = mkinsub("SFO"))
-m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"))
-m_sforb_sfo <- mkinmod(parent = mkinsub("SFORB", "A1"),
-  A1 = mkinsub("SFO"))
-
-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,
- "SFORB-SFO" = m_sforb_sfo),
-  ds_2)
-
-f_nlme_sfo_sfo <- memkin(f_2[1, ])
-f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit
-f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced
-f_nlme_sfo_sfo_4 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink ~ 1)") # further reduced
-\dontrun{
-  f_nlme_sfo_sfo_ff <- memkin(f_2[2, ]) # does not converge with maxIter = 50
-}
-f_nlme_fomc_sfo <- memkin(f_2[3, ])
-\dontrun{
-  f_nlme_dfop_sfo <- memkin(f_2[4, ])  # apparently underdetermined
-  f_nlme_sforb_sfo <- memkin(f_2[5, ]) # also does not converge
-}
-anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo, f_nlme_sfo_sfo_4)
-}
diff --git a/man/mkinsub.Rd b/man/mkinsub.Rd
index 6522a37e..81615a00 100644
--- a/man/mkinsub.Rd
+++ b/man/mkinsub.Rd
@@ -40,11 +40,12 @@ SFO_SFO.2 <- mkinmod(
   parent = mkinsub("SFO", "m1"),
   m1 = mkinsub("SFO"))
 
-# Now supplying full names
-SFO_SFO.2 <- mkinmod(
-  parent = mkinsub("SFO", "m1", full_name = "Test compound"),
-  m1 = mkinsub("SFO", full_name = "Metabolite M1"))
-
+\dontrun{
+  # Now supplying full names
+  SFO_SFO.2 <- mkinmod(
+    parent = mkinsub("SFO", "m1", full_name = "Test compound"),
+    m1 = mkinsub("SFO", full_name = "Metabolite M1"))
+ }
 }
 \author{
 Johannes Ranke
diff --git a/man/nlme.Rd b/man/nlme.Rd
new file mode 100644
index 00000000..e74ba16d
--- /dev/null
+++ b/man/nlme.Rd
@@ -0,0 +1,134 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/nlme.R
+\name{mean_degparms}
+\alias{mean_degparms}
+\alias{nlme_data}
+\alias{nlme_function}
+\title{Estimation of parameter distributions from mmkin row objects}
+\usage{
+mean_degparms(object)
+
+nlme_data(object)
+
+nlme_function(object)
+}
+\arguments{
+\item{object}{An mmkin row object containing several fits of the same model to different datasets}
+}
+\value{
+A named vector containing mean values of the fitted degradation model parameters
+
+A groupedData data object
+
+A function that can be used with nlme
+}
+\description{
+This function sets up and attempts to fit a mixed effects model to
+an mmkin row object. An mmkin row object is essentially a list of mkinfit
+objects that have been obtained by fitting the same model to a list of
+datasets.
+}
+\examples{
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+m_SFO <- mkinmod(parent = mkinsub("SFO"))
+d_SFO_1 <- mkinpredict(m_SFO,
+  c(k_parent_sink = 0.1),
+  c(parent = 98), sampling_times)
+d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
+d_SFO_2 <- mkinpredict(m_SFO,
+  c(k_parent_sink = 0.05),
+  c(parent = 102), sampling_times)
+d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
+d_SFO_3 <- mkinpredict(m_SFO,
+  c(k_parent_sink = 0.02),
+  c(parent = 103), sampling_times)
+d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
+
+d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
+d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
+d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
+ds <- c(d1 = d1, d2 = d2, d3 = d3)
+
+f <- mmkin("SFO", ds, cores = 1, quiet = TRUE)
+mean_dp <- mean_degparms(f)
+grouped_data <- nlme_data(f)
+nlme_f <- nlme_function(f)
+
+library(nlme)
+m_nlme <- nlme(value ~ nlme_f(name, time, parent_0, log_k_parent_sink),
+  data = grouped_data,
+  fixed = parent_0 + log_k_parent_sink ~ 1,
+  random = pdDiag(parent_0 + log_k_parent_sink ~ 1),
+  start = mean_dp)
+summary(m_nlme)
+
+\dontrun{
+  Test on some real data
+  ds_2 <- lapply(experimental_data_for_UBA_2019[6:10],
+   function(x) x$data[c("name", "time", "value")])
+  m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
+    A1 = mkinsub("SFO"), use_of_ff = "min")
+  m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
+    A1 = mkinsub("SFO"), use_of_ff = "max")
+  m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
+    A1 = mkinsub("SFO"))
+  m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
+    A1 = mkinsub("SFO"))
+  m_sforb_sfo <- mkinmod(parent = mkinsub("SFORB", "A1"),
+    A1 = mkinsub("SFO"))
+
+  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,
+   "SFORB-SFO" = m_sforb_sfo),
+    ds_2)
+
+  grouped_data_2 <- nlme_data(f_2["SFO-SFO", ])
+
+  mean_dp_sfo_sfo <- mean_degparms(f_2["SFO-SFO", ])
+  mean_dp_sfo_sfo_ff <- mean_degparms(f_2["SFO-SFO-ff", ])
+  mean_dp_fomc_sfo <- mean_degparms(f_2["FOMC-SFO", ])
+  mean_dp_dfop_sfo <- mean_degparms(f_2["DFOP-SFO", ])
+  mean_dp_sforb_sfo <- mean_degparms(f_2["SFORB-SFO", ])
+
+  nlme_f_sfo_sfo <- nlme_function(f_2["SFO-SFO", ])
+  nlme_f_sfo_sfo_ff <- nlme_function(f_2["SFO-SFO-ff", ])
+  nlme_f_fomc_sfo <- nlme_function(f_2["FOMC-SFO", ])
+
+  # Allowing for correlations between random effects leads to non-convergence
+  f_nlme_sfo_sfo <- nlme(value ~ nlme_f_sfo_sfo(name, time,
+       parent_0, log_k_parent_sink, log_k_parent_A1, log_k_A1_sink),
+     data = grouped_data_2,
+     fixed = parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1,
+     random = pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1),
+     start = mean_dp_sfo_sfo)
+
+  # The same model fitted with transformed formation fractions does not converge
+  f_nlme_sfo_sfo_ff <- nlme(value ~ nlme_f_sfo_sfo_ff(name, time,
+       parent_0, log_k_parent, log_k_A1, f_parent_ilr_1),
+     data = grouped_data_2,
+     fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1,
+     random = pdDiag(parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1),
+     start = mean_dp_sfo_sfo_ff)
+
+  # It does converge with this version of reduced random effects
+  f_nlme_sfo_sfo_ff <- nlme(value ~ nlme_f_sfo_sfo_ff(name, time,
+       parent_0, log_k_parent, log_k_A1, f_parent_ilr_1),
+     data = grouped_data_2,
+     fixed = parent_0 + log_k_parent + log_k_A1 + f_parent_ilr_1 ~ 1,
+     random = pdDiag(parent_0 + log_k_parent ~ 1),
+     start = mean_dp_sfo_sfo_ff)
+
+  f_nlme_fomc_sfo <- nlme(value ~ nlme_f_fomc_sfo(name, time,
+       parent_0, log_alpha, log_beta, log_k_A1, f_parent_ilr_1),
+     data = grouped_data_2,
+     fixed = parent_0 + log_alpha + log_beta + log_k_A1 + f_parent_ilr_1 ~ 1,
+     random = pdDiag(parent_0 + log_alpha + log_beta + log_k_A1 + f_parent_ilr_1 ~ 1),
+     start = mean_dp_fomc_sfo)
+
+  # DFOP-SFO and SFORB-SFO did not converge with full random effects
+
+  anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo)
+}
+}
diff --git a/vignettes/web_only/FOCUS_Z.R b/vignettes/web_only/FOCUS_Z.R
deleted file mode 100644
index 0c19794e..00000000
--- a/vignettes/web_only/FOCUS_Z.R
+++ /dev/null
@@ -1,115 +0,0 @@
-## ---- include = FALSE---------------------------------------------------------
-require(knitr)
-options(digits = 5)
-opts_chunk$set(engine='R', tidy = FALSE)
-
-## ---- echo = TRUE, fig = TRUE, fig.width = 8, fig.height = 7------------------
-library(mkin, quietly = TRUE)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
-
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
-
-## ----FOCUS_2006_Z_fits_1, echo=TRUE, fig.height=6-----------------------------
-Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
-m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.2a)
-summary(m.Z.2a, data = FALSE)$bpar
-
-## ----FOCUS_2006_Z_fits_2, echo=TRUE, fig.height=6-----------------------------
-Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
-
-m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.2a.ff)
-summary(m.Z.2a.ff, data = FALSE)$bpar
-
-## ----FOCUS_2006_Z_fits_3, echo=TRUE, fig.height=6-----------------------------
-Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
-m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.3)
-summary(m.Z.3, data = FALSE)$bpar
-
-## ----FOCUS_2006_Z_fits_5, echo=TRUE, fig.height=7-----------------------------
-Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-               Z2 = mkinsub("SFO"), use_of_ff = "max")
-m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.5)
-
-## ----FOCUS_2006_Z_fits_6, echo=TRUE, fig.height=8-----------------------------
-Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                   Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"),
-                   use_of_ff = "max")
-m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
-plot_sep(m.Z.FOCUS)
-summary(m.Z.FOCUS, data = FALSE)$bpar
-endpoints(m.Z.FOCUS)
-
-## ----FOCUS_2006_Z_fits_7, echo=TRUE, fig.height=8-----------------------------
-Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
-m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.mkin.1)
-summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
-
-## ----FOCUS_2006_Z_fits_9, echo=TRUE, fig.height=8-----------------------------
-Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
-m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
-plot_sep(m.Z.mkin.3)
-
-## ----FOCUS_2006_Z_fits_10, echo=TRUE, fig.height=8----------------------------
-Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
-m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.4)
-
-## ----FOCUS_2006_Z_fits_11, echo=TRUE, fig.height=8----------------------------
-Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
-m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
-plot_sep(m.Z.mkin.5)
-
-## ----FOCUS_2006_Z_fits_11a, echo=TRUE-----------------------------------------
-m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
-plot_sep(m.Z.mkin.5a)
-
-## ----FOCUS_2006_Z_fits_11b, echo=TRUE-----------------------------------------
-mkinparplot(m.Z.mkin.5a)
-
-## ----FOCUS_2006_Z_fits_11b_endpoints, echo=TRUE-------------------------------
-endpoints(m.Z.mkin.5a)
-
diff --git a/vignettes/web_only/compiled_models.R b/vignettes/web_only/compiled_models.R
deleted file mode 100644
index 691037ec..00000000
--- a/vignettes/web_only/compiled_models.R
+++ /dev/null
@@ -1,61 +0,0 @@
-## ---- include = FALSE---------------------------------------------------------
-library(knitr)
-opts_chunk$set(tidy = FALSE, cache = FALSE)
-
-## ----check_gcc, eval = FALSE--------------------------------------------------
-#  pkgbuild::has_compiler()
-
-## ----Rprofile, eval = FALSE---------------------------------------------------
-#  Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";"))
-
-## ----HOME, eval = FALSE-------------------------------------------------------
-#  Sys.getenv("HOME")
-
-## ----create_SFO_SFO-----------------------------------------------------------
-library("mkin", quietly = TRUE)
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
-
-## ----benchmark_SFO_SFO, fig.height = 3, message = FALSE, warning = FALSE------
-if (require(rbenchmark)) {
-  b.1 <- benchmark(
-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
-                                      solution_type = "deSolve",
-                                      use_compiled = FALSE, quiet = TRUE),
-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
-                                 solution_type = "eigen", quiet = TRUE),
-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
-                                  solution_type = "deSolve", quiet = TRUE),
-    replications = 3)
-  print(b.1)
-  factor_SFO_SFO <- round(b.1["1", "relative"])
-} else {
-  factor_SFO_SFO <- NA
-  print("R package rbenchmark is not available")
-}
-
-## ----benchmark_FOMC_SFO, fig.height = 3, warning = FALSE----------------------
-if (require(rbenchmark)) {
-  FOMC_SFO <- mkinmod(
-    parent = mkinsub("FOMC", "m1"),
-    m1 = mkinsub( "SFO"))
-
-  b.2 <- benchmark(
-    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
-                                      use_compiled = FALSE, quiet = TRUE),
-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
-    replications = 3)
-  print(b.2)
-  factor_FOMC_SFO <- round(b.2["1", "relative"])
-} else {
-  factor_FOMC_SFO <- NA
-  print("R package benchmark is not available")
-}
-
-## ----sessionInfo, echo = FALSE------------------------------------------------
-cat(utils::capture.output(utils::sessionInfo())[1:3], sep = "\n")
-if(!inherits(try(cpuinfo <- readLines("/proc/cpuinfo")), "try-error")) {
-  cat(gsub("model name\t: ", "CPU model: ", cpuinfo[grep("model name", cpuinfo)[1]]))
-}
-