nlmixr2 augmented plot

This month I will on a single nlmixr2’s plot function that is shared with nlme, augPred(). I think this is useful but also harder to find like the rxode2 plots discussed last month. The example of this feature is the phenobarbitol data: library(nlmixr2) pheno <- function() { ini({ tcl <- log(0.008) # typical value of clearance tv <- log(0.6) # typical value of volume ## var(eta.cl) eta.cl + eta.v ~ c(1, 0.

By Matthew Fidler in nlmixr2

March 31, 2025

rxode2 plotting

This month I will focus on rxode2’s plotting functions. I think these are very useful but not very well known. In general I will focus on three things: plotting single subjects, plotting multiple subjects and plotting confidence bands. Plot functions rxode2 plotting Of course discussion of plotting require a model and simulation, so we will use the model from the original tutorial: library(rxode2) ## Model from rxode2 tutorial m1 <- rxode2({ KA <- 2.

By Matthew Fidler in rxode2

February 25, 2025

nlmixr2/rxode2 user functions to modify code

This month I will talk about a new type of user function. Previously, I spoke of user functions that you can use in your code to extend the functionality of rxode2 and nlmixr2. Recently we released the ability for certain functions to generate code. I will go over examples that could be helpful to extend rxode2 ui models: An example that allows arguments to be named inside of the rxode2 ui models (though classic models still do not allow this).

By Matthew Fidler in rxode2

January 24, 2025

nlmixr2/rxode2 mu referencing 3.0/4.0

This month, I will talk about about a new iteration of mu-referencing in nlmixr2, which I call mu3 and mu4. What is mu referencing in nlmixr2 – Review from another post From the last blog post about mu-referencing, I will give a brief overview of mu-referencing and what mu-2 referencing is and how it is expanded a bit more. mu-referencing is combining a fixed effect, random effect and possibly a covariate in the form:

babelmixr2 and PopED

New babelmixr2 integrates PopED. I am excited to announce today a new version of babelmixr2 has been released that streamlines creating fast, efficient PopED databases for optimal design. With the babelmixr2 package you can: Import your NONMEM model to rxode2/nlmixr2 format using nonmem2rx Import your Monolix model to rxode2/nlmixr2 using monolix2rx Use your existing nlmixr2 model or create your own rxode2/nlmixr2 model With it in the nlmixr2 format, you can then quickly do optimal design