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-rw-r--r--man/mkinmod.Rd6
-rw-r--r--man/nlme.Rd1
-rw-r--r--man/nlme.mmkin.Rd45
-rw-r--r--man/summary.nlme.mmkin.Rd1
4 files changed, 33 insertions, 20 deletions
diff --git a/man/mkinmod.Rd b/man/mkinmod.Rd
index 77319aac..95cec09a 100644
--- a/man/mkinmod.Rd
+++ b/man/mkinmod.Rd
@@ -155,13 +155,17 @@ print(SFO_SFO)
fit_sfo_sfo <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, solution_type = "deSolve")
# Now supplying compound names used for plotting, and write to user defined location
+ # We need to choose a path outside the session tempdir because this gets removed
+ DLL_dir <- "~/.local/share/mkin"
+ if (!dir.exists(DLL_dir)) dir.create(DLL_dir)
SFO_SFO.2 <- mkinmod(
parent = mkinsub("SFO", "m1", full_name = "Test compound"),
m1 = mkinsub("SFO", full_name = "Metabolite M1"),
- name = "SFO_SFO", dll_dir = "~/dll", unload = TRUE, overwrite = TRUE)
+ name = "SFO_SFO", dll_dir = DLL_dir, unload = TRUE, overwrite = TRUE)
# Now we can save the model and restore it in a new session
saveRDS(SFO_SFO.2, file = "~/SFO_SFO.rds")
# Terminate the R session here if you would like to check, and then do
+library(mkin)
SFO_SFO.3 <- readRDS("~/SFO_SFO.rds")
fit_sfo_sfo <- mkinfit(SFO_SFO.3, FOCUS_2006_D, quiet = TRUE, solution_type = "deSolve")
diff --git a/man/nlme.Rd b/man/nlme.Rd
index df721a0f..307cca82 100644
--- a/man/nlme.Rd
+++ b/man/nlme.Rd
@@ -78,7 +78,6 @@ plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
# The procedure is greatly simplified by the nlme.mmkin function
f_nlme <- nlme(f)
plot(f_nlme)
-
}
\seealso{
\code{\link{nlme.mmkin}}
diff --git a/man/nlme.mmkin.Rd b/man/nlme.mmkin.Rd
index abcd0e81..0a9f6913 100644
--- a/man/nlme.mmkin.Rd
+++ b/man/nlme.mmkin.Rd
@@ -87,15 +87,15 @@ ds <- lapply(experimental_data_for_UBA_2019[6:10],
f <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, cores = 1)
library(nlme)
f_nlme_sfo <- nlme(f["SFO", ])
-f_nlme_dfop <- nlme(f["DFOP", ])
-AIC(f_nlme_sfo, f_nlme_dfop)
-print(f_nlme_dfop)
-plot(f_nlme_dfop)
-endpoints(f_nlme_dfop)
\dontrun{
- f_nlme_2 <- nlme(f["SFO", ], start = c(parent_0 = 100, log_k_parent = 0.1))
- update(f_nlme_2, random = parent_0 ~ 1)
+
+ f_nlme_dfop <- nlme(f["DFOP", ])
+ anova(f_nlme_sfo, f_nlme_dfop)
+ print(f_nlme_dfop)
+ plot(f_nlme_dfop)
+ endpoints(f_nlme_dfop)
+
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"),
@@ -113,14 +113,15 @@ endpoints(f_nlme_dfop)
f_nlme_sfo_sfo <- nlme(f_2["SFO-SFO", ])
plot(f_nlme_sfo_sfo)
- # With formation fractions
- f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
- plot(f_nlme_sfo_sfo_ff)
+ # With formation fractions this does not coverge with defaults
+ # f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
+ #plot(f_nlme_sfo_sfo_ff)
- # For the following fit we need to increase pnlsMaxIter and the tolerance
- # to get convergence
- f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
- control = list(pnlsMaxIter = 120, tolerance = 5e-4), verbose = TRUE)
+ # With the log-Cholesky parameterization, this converges in 11
+ # iterations and around 100 seconds, but without tweaking control
+ # parameters (with pdDiag, increasing the tolerance and pnlsMaxIter was
+ # necessary)
+ f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ])
plot(f_nlme_dfop_sfo)
@@ -145,10 +146,18 @@ endpoints(f_nlme_dfop)
ds_2, quiet = TRUE, error_model = "obs")
f_nlme_sfo_sfo_obs <- nlme(f_2_obs["SFO-SFO", ])
print(f_nlme_sfo_sfo_obs)
- # The same with DFOP-SFO does not converge, apparently the variances of
- # parent and A1 are too similar in this case, so that the model is
- # overparameterised
- #f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ], control = list(maxIter = 100))
+ f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ])
+
+ f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo,
+ "DFOP-SFO" = m_dfop_sfo),
+ ds_2, quiet = TRUE, error_model = "tc")
+ # f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # stops with error message
+ f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ])
+ # We get warnings about false convergence in the LME step in several iterations
+ # but as the last such warning occurs in iteration 25 and we have 28 iterations
+ # we can ignore these
+ anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs, f_nlme_dfop_sfo_tc)
+
}
}
\seealso{
diff --git a/man/summary.nlme.mmkin.Rd b/man/summary.nlme.mmkin.Rd
index ea625dd7..d7e61074 100644
--- a/man/summary.nlme.mmkin.Rd
+++ b/man/summary.nlme.mmkin.Rd
@@ -80,6 +80,7 @@ pred_sfo <- function(k) {
ds_sfo_mean <- lapply(k_in, pred_sfo)
names(ds_sfo_mean) <- paste("ds", 1:5)
+set.seed(12345)
ds_sfo_syn <- lapply(ds_sfo_mean, function(ds) {
add_err(ds,
sdfunc = function(value) sqrt(1^2 + value^2 * 0.07^2),

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