Remove nlmixr interface for release of mkin 1.1.0

I am postponing my attempts to get the nlmixr interface to CRAN, given
some problems with nlmixr using R-devel under Windows, see
https://github.com/nlmixrdevelopment/nlmixr/issues/596
and
https://github.com/r-hub/rhub/issues/512,
which is fixed by the removal of nlmixr from the testsuite.

For the tests to be more platform independent, the biphasic mixed
effects models test dataset was defined in a way that fitting
should be more robust (less ill-defined).

1 files changed, 0 insertions, 245 deletions

diff --git a/man/nlmixr.mmkin.Rd b/man/nlmixr.mmkin.Rd
deleted file mode 100644
index c1a203eb..00000000
--- a/man/nlmixr.mmkin.Rd
+++ /dev/null
@@ -1,245 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/nlmixr.R
-\name{nlmixr.mmkin}
-\alias{nlmixr.mmkin}
-\alias{print.nlmixr.mmkin}
-\alias{nlmixr_model}
-\alias{nlmixr_data}
-\title{Fit nonlinear mixed models using nlmixr}
-\usage{
-\method{nlmixr}{mmkin}(
-  object,
-  data = NULL,
-  est = NULL,
-  control = list(),
-  table = tableControl(),
-  error_model = object[[1]]$err_mod,
-  test_log_parms = TRUE,
-  conf.level = 0.6,
-  degparms_start = "auto",
-  eta_start = "auto",
-  ...,
-  save = NULL,
-  envir = parent.frame()
-)
-
-\method{print}{nlmixr.mmkin}(x, digits = max(3, getOption("digits") - 3), ...)
-
-nlmixr_model(
-  object,
-  est = c("saem", "focei"),
-  degparms_start = "auto",
-  eta_start = "auto",
-  test_log_parms = TRUE,
-  conf.level = 0.6,
-  error_model = object[[1]]$err_mod,
-  add_attributes = FALSE
-)
-
-nlmixr_data(object, ...)
-}
-\arguments{
-\item{object}{An \link{mmkin} row object containing several fits of the same
-\link{mkinmod} model to different datasets}
-
-\item{data}{Not used, as the data are extracted from the mmkin row object}
-
-\item{est}{Estimation method passed to \link[nlmixr:nlmixr]{nlmixr::nlmixr}}
-
-\item{control}{Passed to \link[nlmixr:nlmixr]{nlmixr::nlmixr}}
-
-\item{table}{Passed to \link[nlmixr:nlmixr]{nlmixr::nlmixr}}
-
-\item{error_model}{Optional argument to override the error model which is
-being set based on the error model used in the mmkin row object.}
-
-\item{test_log_parms}{If TRUE, an attempt is made to use more robust starting
-values for population parameters fitted as log parameters in mkin (like
-rate constants) by only considering rate constants that pass the t-test
-when calculating mean degradation parameters using \link{mean_degparms}.}
-
-\item{conf.level}{Possibility to adjust the required confidence level
-for parameter that are tested if requested by 'test_log_parms'.}
-
-\item{degparms_start}{Parameter values given as a named numeric vector will
-be used to override the starting values obtained from the 'mmkin' object.}
-
-\item{eta_start}{Standard deviations on the transformed scale given as a
-named numeric vector will be used to override the starting values obtained
-from the 'mmkin' object.}
-
-\item{\dots}{Passed to \link{nlmixr_model}}
-
-\item{save}{Passed to \link[nlmixr:nlmixr]{nlmixr::nlmixr}}
-
-\item{envir}{Passed to \link[nlmixr:nlmixr]{nlmixr::nlmixr}}
-
-\item{x}{An nlmixr.mmkin object to print}
-
-\item{digits}{Number of digits to use for printing}
-
-\item{add_attributes}{Should the starting values used for degradation model
-parameters and their distribution and for the error model parameters
-be returned as attributes?}
-}
-\value{
-An S3 object of class 'nlmixr.mmkin', containing the fitted
-\link[nlmixr:nlmixr]{nlmixr::nlmixr} object as a list component named 'nm'. The
-object also inherits from 'mixed.mmkin'.
-
-An function defining a model suitable for fitting with \link[nlmixr:nlmixr]{nlmixr::nlmixr}.
-
-An dataframe suitable for use with \link[nlmixr:nlmixr]{nlmixr::nlmixr}
-}
-\description{
-This function uses \code{\link[nlmixr:nlmixr]{nlmixr::nlmixr()}} as a backend for fitting nonlinear mixed
-effects models created from \link{mmkin} row objects using the Stochastic Approximation
-Expectation Maximisation algorithm (SAEM) or First Order Conditional
-Estimation with Interaction (FOCEI).
-}
-\details{
-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 using \link{mkinfit}.
-}
-\examples{
-\dontrun{
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
-
-f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP", "HS"), ds, quiet = TRUE, cores = 1)
-f_mmkin_parent_tc <- mmkin(c("SFO", "FOMC", "DFOP"), ds, error_model = "tc",
-  cores = 1, quiet = TRUE)
-
-library(nlmixr)
-f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem",
-  control = saemControl(print = 0))
-f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei",
-  control = foceiControl(print = 0))
-
-f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem",
-  control = saemControl(print = 0))
-f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei",
-  control = foceiControl(print = 0))
-
-f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem",
-  control = saemControl(print = 0))
-f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei",
-  control = foceiControl(print = 0))
-
-f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem",
-  control = saemControl(print = 0))
-f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei",
-  control = foceiControl(print = 0))
-
-f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem",
-  control = saemControl(print = 0))
-f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei",
-  control = foceiControl(print = 0))
-
-AIC(
-  f_nlmixr_sfo_saem$nm, f_nlmixr_sfo_focei$nm,
-  f_nlmixr_fomc_saem$nm, f_nlmixr_fomc_focei$nm,
-  f_nlmixr_dfop_saem$nm, f_nlmixr_dfop_focei$nm,
-  f_nlmixr_hs_saem$nm, f_nlmixr_hs_focei$nm,
-  f_nlmixr_fomc_saem_tc$nm, f_nlmixr_fomc_focei_tc$nm)
-
-AIC(nlme(f_mmkin_parent["FOMC", ]))
-AIC(nlme(f_mmkin_parent["HS", ]))
-
-# The FOCEI fit of FOMC with constant variance or the tc error model is best
-plot(f_nlmixr_fomc_saem_tc)
-
-sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-
-f_mmkin_const <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE, error_model = "const")
-f_mmkin_obs <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE, error_model = "obs")
-f_mmkin_tc <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE, error_model = "tc")
-
-nlmixr_model(f_mmkin_const["SFO-SFO", ])
-
-# A single constant variance is currently only possible with est = 'focei' in nlmixr
-f_nlmixr_sfo_sfo_focei_const <- nlmixr(f_mmkin_const["SFO-SFO", ], est = "focei")
-f_nlmixr_fomc_sfo_focei_const <- nlmixr(f_mmkin_const["FOMC-SFO", ], est = "focei")
-f_nlmixr_dfop_sfo_focei_const <- nlmixr(f_mmkin_const["DFOP-SFO", ], est = "focei")
-
-# Variance by variable is supported by 'saem' and 'focei'
-f_nlmixr_fomc_sfo_saem_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "saem")
-f_nlmixr_fomc_sfo_focei_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "focei")
-f_nlmixr_dfop_sfo_saem_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "saem")
-f_nlmixr_dfop_sfo_focei_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "focei")
-
-# Identical two-component error for all variables is only possible with
-# est = 'focei' in nlmixr
-f_nlmixr_fomc_sfo_focei_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei")
-f_nlmixr_dfop_sfo_focei_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei")
-
-# Two-component error by variable is possible with both estimation methods
-# Variance by variable is supported by 'saem' and 'focei'
-f_nlmixr_fomc_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "saem",
-  error_model = "obs_tc")
-f_nlmixr_fomc_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei",
-  error_model = "obs_tc")
-f_nlmixr_dfop_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "saem",
-  error_model = "obs_tc")
-f_nlmixr_dfop_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei",
-  error_model = "obs_tc")
-
-AIC(
-  f_nlmixr_sfo_sfo_focei_const$nm,
-  f_nlmixr_fomc_sfo_focei_const$nm,
-  f_nlmixr_dfop_sfo_focei_const$nm,
-  f_nlmixr_fomc_sfo_saem_obs$nm,
-  f_nlmixr_fomc_sfo_focei_obs$nm,
-  f_nlmixr_dfop_sfo_saem_obs$nm,
-  f_nlmixr_dfop_sfo_focei_obs$nm,
-  f_nlmixr_fomc_sfo_focei_tc$nm,
-  f_nlmixr_dfop_sfo_focei_tc$nm,
-  f_nlmixr_fomc_sfo_saem_obs_tc$nm,
-  f_nlmixr_fomc_sfo_focei_obs_tc$nm,
-  f_nlmixr_dfop_sfo_saem_obs_tc$nm,
-  f_nlmixr_dfop_sfo_focei_obs_tc$nm
-)
-# Currently, FOMC-SFO with two-component error by variable fitted by focei gives the
-# lowest AIC
-plot(f_nlmixr_fomc_sfo_focei_obs_tc)
-summary(f_nlmixr_fomc_sfo_focei_obs_tc)
-
-# Two parallel metabolites
-dmta_ds <- lapply(1:7, 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[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
-sfo_sfo2 <- mkinmod(
-  DMTA = mkinsub("SFO", c("M23", "M27")),
-  M23 = mkinsub("SFO"),
-  M27 = mkinsub("SFO"),
-  quiet = TRUE
-)
-f_dmta_sfo_sfo2 <- mmkin(
-  list("SFO-SFO2" = sfo_sfo2),
-  dmta_ds, quiet = TRUE, error_model = "obs")
-nlmixr_model(f_dmta_sfo_sfo2)
-nlmixr_focei_dmta_sfo_sfo2 <- nlmixr(f_dmta_sfo_sfo2, est = "focei")
-}
-}
-\seealso{
-\link{summary.nlmixr.mmkin} \link{plot.mixed.mmkin}
-}