From 26085403289e29259e500282e8e88a5ab00c07a0 Mon Sep 17 00:00:00 2001
From: Johannes Ranke <jranke@uni-bremen.de>
Date: Tue, 14 Apr 2020 17:22:00 +0200
Subject: Add a nlme method for mmkin row objects

---
 man/nlme.Rd       | 15 +++++-------
 man/nlme.mmkin.Rd | 72 +++++++++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 78 insertions(+), 9 deletions(-)
 create mode 100644 man/nlme.mmkin.Rd

(limited to 'man')

diff --git a/man/nlme.Rd b/man/nlme.Rd
index 8e5c2aa0..971ba3f5 100644
--- a/man/nlme.Rd
+++ b/man/nlme.Rd
@@ -101,14 +101,19 @@ plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
   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", ])
+  assign("nlme_f_sfo_sfo", nlme_f_sfo_sfo, globalenv())
+  assign("nlme_f_sfo_sfo_ff", nlme_f_sfo_sfo_ff, globalenv())
+  assign("nlme_f_fomc_sfo", nlme_f_fomc_sfo, globalenv())
 
-  # Allowing for correlations between random effects leads to non-convergence
+  # Allowing for correlations between random effects (not shown)
+  # 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)
+   # augPred does not see to work on this object, so no plot is shown
 
   # 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,
@@ -118,14 +123,6 @@ plot(augPred(m_nlme, level = 0:1), layout = c(3, 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,
diff --git a/man/nlme.mmkin.Rd b/man/nlme.mmkin.Rd
new file mode 100644
index 00000000..5f937488
--- /dev/null
+++ b/man/nlme.mmkin.Rd
@@ -0,0 +1,72 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/nlme.mmkin.R
+\name{nlme.mmkin}
+\alias{nlme.mmkin}
+\title{Create an nlme model for an mmkin row object}
+\usage{
+\method{nlme}{mmkin}(
+  model,
+  data = sys.frame(sys.parent()),
+  fixed,
+  random = fixed,
+  groups,
+  start,
+  correlation = NULL,
+  weights = NULL,
+  subset,
+  method = c("ML", "REML"),
+  na.action = na.fail,
+  naPattern,
+  control = list(),
+  verbose = FALSE
+)
+}
+\arguments{
+\item{model}{An \code{\link{mmkin}} row object.}
+
+\item{data}{Ignored, data are taken from the mmkin model}
+
+\item{fixed}{Ignored, all degradation parameters fitted in the
+mmkin model are used as fixed parameters}
+
+\item{random}{If not specified, all fixed effects are complemented
+with uncorrelated random effects}
+
+\item{groups}{See the documentation of nlme}
+
+\item{start}{If not specified, mean values of the fitted degradation
+parameters taken from the mmkin object are used}
+
+\item{correlation}{See the documentation of nlme}
+
+\item{weights}{passed to nlme}
+
+\item{subset}{passed to nlme}
+
+\item{method}{passed to nlme}
+
+\item{na.action}{passed to nlme}
+
+\item{naPattern}{passed to nlme}
+
+\item{control}{passed to nlme}
+
+\item{verbose}{passed to nlme}
+}
+\value{
+Upon success, a fitted nlme.mmkin object, which is
+  an nlme object with additional elements
+}
+\description{
+Create an nlme model for an mmkin row object
+}
+\examples{
+ds <- lapply(experimental_data_for_UBA_2019[6:10],
+ function(x) subset(x$data[c("name", "time", "value")], name == "parent"))
+f <- mmkin("SFO", ds, quiet = TRUE, cores = 1)
+library(nlme)
+f_nlme <- nlme(f)
+nlme(f, random = parent_0 ~ 1)
+f_nlme <- nlme(f, start = c(parent_0 = 100, log_k_parent_sink = 0.1))
+update(f_nlme, random = parent_0 ~ 1)
+}
-- 
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