pkbuild | R Documentation |
Fit several structural PK models and select the best one based on a Bayesian Information Criterion. Models to compare can be defined by rate constants and/or clearances and can include or not nonlinear elimination models. See https://monolix.lixoft.com/rsmlx/pkbuild/ for more details.
pkbuild(
data = NULL,
project = NULL,
stat = FALSE,
param = "clearance",
new.dir = ".",
MM = FALSE,
linearization = F,
criterion = "BICc",
level = NULL,
settings.stat = NULL
)
data |
a list with fields
|
project |
a Monolix project |
stat |
(FALSE, TRUE): the statistical model is also built (using buildmlx) (default=FALSE) |
param |
("clearance", "rate", "both): parametrization (default="clearance") |
new.dir |
name of the directory where the created files are stored (default is the current working directory) ) |
MM |
(FALSE, TRUE): tested models include or not Michaelis Menten elimination models (default=FALSE) |
linearization |
TRUE/FALSE whether the computation of the likelihood is based on a linearization of the model (default=FALSE) |
criterion |
penalization criterion to optimize c("AIC", "BIC", "BICc", gamma) (default="BICc") |
level |
an integer between 1 and 9 (used by setSettings) |
settings.stat |
list of settings used by buildmlx (only if stat=TRUE) |
A list of results
## Not run:
# Build a PK model for the warfarin PK data.
# By default, only models using clearance (and inter compartmental clearances) are used
warf.pk1 <- pkbuild(data=warfarin)
# Models using elimination and transfer rate constants are used,
# as well as nonlinear elimination models
warf.pk2 <- pkbuild(data=warfarin, new.dir="warfarin", param="rate", MM=TRUE)
# Both models using clearances and rates are used.
# Level is set to 7 in order to get accurate results.
warf.pk3 <- pkbuild(data=warfarin, new.dir="warfarin", param="both", level=7)
## End(Not run)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.