Vignettes, development ideas and announcements about mrgsolve.
If your mrgsolve model is a translation of a completed NONMEM model run, you can validate it every time; find out how.
Sometimes, you want to stop a simulation that is running (or might run) longer than you want. Find out how.
mrgsolve celebrates her version 1.0.0 release. Find out about some very cool and powerful features that we included in this release.
This blog post will show you how to use a single model to do both population simulation and simulation from a specific set of empirical Bayes estimates. The basic implementation for this approach was pioneered by Tim Waterhouse at MetrumRG.
Find out what’s new in mrgsolve version 0.11.0 and 0.11.1.
Find out what’s new in mrgsolve version 0.10.7.
Find out what’s new in mrgsolve version 0.10.0 and 0.10.1.
Starting with version 0.10.0, mrgsolve can implement dosing records calling for a zero-order infusion at steady state. Find out more in this blog post.
This blog post describes the mechanism by which mrgsolve finds steady state under this new change set (starting late 2019 to early 2020) and describes some of the settings that users can control to their advantage.
In this post, we’ll look at different ways you can bring time after dose into your simulated outputs.
A fun syntax for creating event objects for different dosing regimens.
In this blog post, we run some simulations with mrgsolve and the excellent pmxTools package and compare results.
I came up with this fun model specification format that looks just like Rmarkdown code chunks.
I worked an example for a SIR model to show people in the ecology field how they can use mrgsolve for their ODE-based models.
This post is to introduce modeled interventions in mrgsolve. The main use case is to force mrgsolve to advance the system to a specific time so that some aspect of the system can change at that time.
This is just a post on a simplified implementation of modeled events in mrgsolve. There is also another, more complete blog post on this topic published previously .
Introducing a new model block ($PRED) that lets you write models with analytical solutions.
$PRED
An important mechanism for creating robust, complex simulations is the input data set. In this blog post, we’ll look at some ways you can quickly create input data sets for your simulation.
In this post, we’ll look at how you can code up a mixture model in mrgsolve.
We had a user who was learning mrgsolve ask for a “complete example”. I wasn’t sure what exactly that meant, but I created this example and I’m sharing it today on the blog.
mrgsolve
This post demonstrates that random simulation outputs can be made reproducible by using set.seed().
set.seed()
This tutorial illustrates now to do MAP Bayes estimation with mrgsolve.
This is a shortened version of map_bayes.html, showing only the estimation step.
event objects are data.frame-like data structures that allow you to quickly and flexibly include dosing interventions into your simulations.
There are several ways to set initial conditions in mrgsolve. Find out how this can work to your advantage when planning your simulations.