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-rw-r--r--man/nlme.Rd78
-rw-r--r--man/nlme.mmkin.Rd63
-rw-r--r--man/plot.mmkin.Rd3
-rw-r--r--man/plot.nlme.mmkin.Rd15
4 files changed, 86 insertions, 73 deletions
diff --git a/man/nlme.Rd b/man/nlme.Rd
index f31c7a4f..4a668ac0 100644
--- a/man/nlme.Rd
+++ b/man/nlme.Rd
@@ -8,17 +8,22 @@
\usage{
nlme_function(object)
-mean_degparms(object)
+mean_degparms(object, random = FALSE)
nlme_data(object)
}
\arguments{
\item{object}{An mmkin row object containing several fits of the same model to different datasets}
+
+\item{random}{Should a list with fixed and random effects be returned?}
}
\value{
A function that can be used with nlme
-A named vector containing mean values of the fitted degradation model parameters
+If random is FALSE (default), a named vector containing mean values
+ of the fitted degradation model parameters. If random is TRUE, a list with
+ fixed and random effects, in the format required by the start argument of
+ nlme for the case of a single grouping variable ds?
A \code{\link{groupedData}} object
}
@@ -67,71 +72,10 @@ m_nlme <- nlme(value ~ nlme_f(name, time, parent_0, log_k_parent_sink),
start = mean_dp)
summary(m_nlme)
plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
+# augPred does not seem to work on fits with more than one state
+# variable
-\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", ])
- 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 (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,
- 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)
-
- 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)
}
+\seealso{
+\code{\link{nlme.mmkin}}
}
diff --git a/man/nlme.mmkin.Rd b/man/nlme.mmkin.Rd
index 1fecb5dd..26dcce66 100644
--- a/man/nlme.mmkin.Rd
+++ b/man/nlme.mmkin.Rd
@@ -2,6 +2,8 @@
% Please edit documentation in R/nlme.mmkin.R
\name{nlme.mmkin}
\alias{nlme.mmkin}
+\alias{print.nlme.mmkin}
+\alias{update.nlme.mmkin}
\title{Create an nlme model for an mmkin row object}
\usage{
\method{nlme}{mmkin}(
@@ -20,11 +22,15 @@
control = list(),
verbose = FALSE
)
+
+\method{print}{nlme.mmkin}(x, ...)
+
+\method{update}{nlme.mmkin}(object, ...)
}
\arguments{
\item{model}{An \code{\link{mmkin}} row object.}
-\item{data}{Ignored, data are taken from the mmkin model}
+\item{data}{Should the data be printed?}
\item{fixed}{Ignored, all degradation parameters fitted in the
mmkin model are used as fixed parameters}
@@ -52,6 +58,12 @@ parameters taken from the mmkin object are used}
\item{control}{passed to nlme}
\item{verbose}{passed to nlme}
+
+\item{x}{An nlme.mmkin object to print}
+
+\item{...}{Update specifications passed to update.nlme}
+
+\item{object}{An nlme.mmkin object to update}
}
\value{
Upon success, a fitted nlme.mmkin object, which is an nlme object
@@ -68,9 +80,52 @@ ds <- lapply(experimental_data_for_UBA_2019[6:10],
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)
+print(f_nlme)
+f_nlme_2 <- nlme(f, start = c(parent_0 = 100, log_k_parent_sink = 0.1))
+update(f_nlme_2, random = parent_0 ~ 1)
+\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", quiet = TRUE)
+ m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
+ A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
+ m_fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
+ A1 = mkinsub("SFO"), quiet = TRUE)
+ m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
+ A1 = mkinsub("SFO"), quiet = TRUE)
+
+ 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),
+ ds_2, quiet = TRUE)
+ plot(f_2["SFO-SFO", 3:4]) # Separate fits for datasets 3 and 4
+
+ f_nlme_sfo_sfo <- nlme(f_2["SFO-SFO", ])
+ # plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures
+ plot(f_nlme_sfo_sfo, 3:4) # Global mixed model: Fits for datasets 3 and 4
+
+ # With formation fractions
+ f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
+ plot(f_nlme_sfo_sfo_ff, 3:4) # chi2 different due to different df attribution
+
+ # For more parameters, we need to increase pnlsMaxIter and the tolerance
+ # to get convergence
+ f_nlme_fomc_sfo <- nlme(f_2["FOMC-SFO", ],
+ control = list(pnlsMaxIter = 100, tolerance = 1e-4), verbose = TRUE)
+ f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
+ control = list(pnlsMaxIter = 120, tolerance = 5e-4), verbose = TRUE)
+ plot(f_2["FOMC-SFO", 3:4])
+ plot(f_nlme_fomc_sfo, 3:4)
+
+ plot(f_2["DFOP-SFO", 3:4])
+ plot(f_nlme_dfop_sfo, 3:4)
+
+ anova(f_nlme_dfop_sfo, f_nlme_fomc_sfo, f_nlme_sfo_sfo)
+ anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo) # if we ignore FOMC
+}
}
\seealso{
\code{\link{nlme_function}}
diff --git a/man/plot.mmkin.Rd b/man/plot.mmkin.Rd
index 982e8db6..600881ea 100644
--- a/man/plot.mmkin.Rd
+++ b/man/plot.mmkin.Rd
@@ -33,7 +33,7 @@ column.}
values, with the error model, using \code{\link{mkinerrplot}}.}
\item{standardized}{Should the residuals be standardized? This option
-is passed to \code{\link{mkinresplot}}, it only takes effect if
+is passed to \code{\link{mkinresplot}}, it only takes effect if
`resplot = "time"`.}
\item{show_errmin}{Should the chi2 error level be shown on top of the plots
@@ -76,6 +76,7 @@ latex is being used for the formatting of the chi2 error level.
cores = 1, quiet = TRUE, error_model = "tc")
plot(fits[, "FOCUS C"])
plot(fits["FOMC", ])
+ plot(fits["FOMC", ], show_errmin = FALSE)
# We can also plot a single fit, if we like the way plot.mmkin works, but then the plot
# height should be smaller than the plot width (this is not possible for the html pages
diff --git a/man/plot.nlme.mmkin.Rd b/man/plot.nlme.mmkin.Rd
index c0e749aa..9bea7013 100644
--- a/man/plot.nlme.mmkin.Rd
+++ b/man/plot.nlme.mmkin.Rd
@@ -11,6 +11,9 @@
legends = 1,
resplot = c("time", "errmod"),
standardized = FALSE,
+ show_errmin = TRUE,
+ errmin_var = "All data",
+ errmin_digits = 3,
cex = 0.7,
rel.height.middle = 0.9,
ymax = "auto",
@@ -35,6 +38,15 @@ values, with the error model, using \code{\link{mkinerrplot}}.}
is passed to \code{\link{mkinresplot}}, it only takes effect if
`resplot = "time"`.}
+\item{show_errmin}{Should the chi2 error level be shown on top of the plots
+to the left?}
+
+\item{errmin_var}{The variable for which the FOCUS chi2 error value should
+be shown.}
+
+\item{errmin_digits}{The number of significant digits for rounding the FOCUS
+chi2 error percentage.}
+
\item{cex}{Passed to the plot functions and \code{\link{mtext}}.}
\item{rel.height.middle}{The relative height of the middle plot, if more
@@ -56,11 +68,12 @@ 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)
#plot(f) # too many panels for pkgdown
+plot(f[, 3:4])
library(nlme)
f_nlme <- nlme(f)
#plot(f_nlme) # too many panels for pkgdown
-plot(f_nlme, 1:2)
+plot(f_nlme, 3:4)
}
\author{
Johannes Ranke

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