diff options
Diffstat (limited to 'man')
| -rw-r--r-- | man/memkin.Rd | 84 | ||||
| -rw-r--r-- | man/mkinsub.Rd | 11 | ||||
| -rw-r--r-- | man/nlme.Rd | 134 |
3 files changed, 140 insertions, 89 deletions
diff --git a/man/memkin.Rd b/man/memkin.Rd deleted file mode 100644 index 8ae6100a..00000000 --- a/man/memkin.Rd +++ /dev/null @@ -1,84 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/memkin.R -\name{memkin} -\alias{memkin} -\title{Estimation of parameter distributions from mmkin row objects} -\usage{ -memkin(object, random_spec = "auto", ...) -} -\arguments{ -\item{object}{An mmkin row object containing several fits of the same model to different datasets} - -\item{random_spec}{Either "auto" or a specification of random effects for \code{\link{nlme}} -given as a character vector} - -\item{...}{Additional arguments passed to \code{\link{nlme}}} -} -\value{ -An nlme object -} -\description{ -This function sets up and attempts to fit a mixed effects model to -an mmkin row object which is essentially a list of mkinfit objects -that have been obtained by fitting the same model to a list of -datasets. -} -\examples{ -sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) -m_SFO <- mkinmod(parent = mkinsub("SFO")) -d_SFO_1 <- mkinpredict(m_SFO, - c(k_parent_sink = 0.1), - c(parent = 98), sampling_times) -d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time") -d_SFO_2 <- mkinpredict(m_SFO, - c(k_parent_sink = 0.05), - c(parent = 102), sampling_times) -d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time") -d_SFO_3 <- mkinpredict(m_SFO, - c(k_parent_sink = 0.02), - c(parent = 103), sampling_times) -d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time") - -d1 <- add_err(d_SFO_1, function(value) 3, n = 1) -d2 <- add_err(d_SFO_2, function(value) 2, n = 1) -d3 <- add_err(d_SFO_3, function(value) 4, n = 1) -ds <- c(d1 = d1, d2 = d2, d3 = d3) - -f <- mmkin("SFO", ds) -x <- memkin(f) -summary(x) - -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) - -f_nlme_sfo_sfo <- memkin(f_2[1, ]) -f_nlme_sfo_sfo_2 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 + log_k_A1_sink ~ 1)") # explicit -f_nlme_sfo_sfo_3 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink + log_k_parent_A1 ~ 1)") # reduced -f_nlme_sfo_sfo_4 <- memkin(f_2[1, ], "pdDiag(parent_0 + log_k_parent_sink ~ 1)") # further reduced -\dontrun{ - f_nlme_sfo_sfo_ff <- memkin(f_2[2, ]) # does not converge with maxIter = 50 -} -f_nlme_fomc_sfo <- memkin(f_2[3, ]) -\dontrun{ - f_nlme_dfop_sfo <- memkin(f_2[4, ]) # apparently underdetermined - f_nlme_sforb_sfo <- memkin(f_2[5, ]) # also does not converge -} -anova(f_nlme_fomc_sfo, f_nlme_sfo_sfo, f_nlme_sfo_sfo_4) -} diff --git a/man/mkinsub.Rd b/man/mkinsub.Rd index 6522a37e..81615a00 100644 --- a/man/mkinsub.Rd +++ b/man/mkinsub.Rd @@ -40,11 +40,12 @@ SFO_SFO.2 <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO")) -# Now supplying full names -SFO_SFO.2 <- mkinmod( - parent = mkinsub("SFO", "m1", full_name = "Test compound"), - m1 = mkinsub("SFO", full_name = "Metabolite M1")) - +\dontrun{ + # Now supplying full names + SFO_SFO.2 <- mkinmod( + parent = mkinsub("SFO", "m1", full_name = "Test compound"), + m1 = mkinsub("SFO", full_name = "Metabolite M1")) + } } \author{ Johannes Ranke diff --git a/man/nlme.Rd b/man/nlme.Rd new file mode 100644 index 00000000..e74ba16d --- /dev/null +++ b/man/nlme.Rd @@ -0,0 +1,134 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/nlme.R +\name{mean_degparms} +\alias{mean_degparms} +\alias{nlme_data} +\alias{nlme_function} +\title{Estimation of parameter distributions from mmkin row objects} +\usage{ +mean_degparms(object) + +nlme_data(object) + +nlme_function(object) +} +\arguments{ +\item{object}{An mmkin row object containing several fits of the same model to different datasets} +} +\value{ +A named vector containing mean values of the fitted degradation model parameters + +A groupedData data object + +A function that can be used with nlme +} +\description{ +This function sets up and attempts to fit a mixed effects model to +an mmkin row object. 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. +} +\examples{ +sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) +m_SFO <- mkinmod(parent = mkinsub("SFO")) +d_SFO_1 <- mkinpredict(m_SFO, + c(k_parent_sink = 0.1), + c(parent = 98), sampling_times) +d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time") +d_SFO_2 <- mkinpredict(m_SFO, + c(k_parent_sink = 0.05), + c(parent = 102), sampling_times) +d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time") +d_SFO_3 <- mkinpredict(m_SFO, + c(k_parent_sink = 0.02), + c(parent = 103), sampling_times) +d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time") + +d1 <- add_err(d_SFO_1, function(value) 3, n = 1) +d2 <- add_err(d_SFO_2, function(value) 2, n = 1) +d3 <- add_err(d_SFO_3, function(value) 4, n = 1) +ds <- c(d1 = d1, d2 = d2, d3 = d3) + +f <- mmkin("SFO", ds, cores = 1, quiet = TRUE) +mean_dp <- mean_degparms(f) +grouped_data <- nlme_data(f) +nlme_f <- nlme_function(f) + +library(nlme) +m_nlme <- nlme(value ~ nlme_f(name, time, parent_0, log_k_parent_sink), + data = grouped_data, + fixed = parent_0 + log_k_parent_sink ~ 1, + random = pdDiag(parent_0 + log_k_parent_sink ~ 1), + start = mean_dp) +summary(m_nlme) + +\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", ]) + + # Allowing for correlations between random effects 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) + + # 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) + + # 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, + 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) +} +} |