diff options
Diffstat (limited to 'man/nlme.mmkin.Rd')
-rw-r--r-- | man/nlme.mmkin.Rd | 63 |
1 files changed, 59 insertions, 4 deletions
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}} |