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authorJohannes Ranke <jranke@uni-bremen.de>2020-04-14 17:22:00 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2020-04-14 17:22:00 +0200
commit26085403289e29259e500282e8e88a5ab00c07a0 (patch)
treee86d5195c725ee0c08a45e4393ff9c1dfad64314 /man/nlme.mmkin.Rd
parentd4a49b4837de347d34b2c198de7342c34b0fab63 (diff)
Add a nlme method for mmkin row objects
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+% 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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