mrgsolve/blog - mrgsolve blog

Stopping long-running simulations

Sometimes, you want to stop a simulation that is running (or might run) longer than you want. Find out how.

New in version 1.0.0

mrgsolve celebrates her version 1.0.0 release. Find out about some very cool and powerful features that we included in this release.

Simulate From EBE

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…

New in 0.11.0 and 0.11.1

Find out what’s new in mrgsolve version 0.11.0 and 0.11.1.

New in 0.10.7

Find out what’s new in mrgsolve version 0.10.7.

New in 0.10.0 and 0.10.1

Find out what’s new in mrgsolve version 0.10.0 and 0.10.1.

Zero-order steady state infusion

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.

Steady State in mrgsolve

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…

Time after dose (TAD)

time after dose

In this post, we’ll look at different ways you can bring time after dose into your simulated outputs.

Alternate dosing event syntax

A fun syntax for creating event objects for different dosing regimens.

Validating Simulation Results with pmxTools

In this blog post, we run some simulations with mrgsolve and the excellent pmxTools package and compare results.

Rmarkdown model specification

model specification

I came up with this fun model specification format that looks just like Rmarkdown code chunks.

Tidy workflow for simulating dynamics in R

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.

Modeled interventions in mrgsolve

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…

mtime

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 .

Models without compartments

model specification

Introducing a new model block ($PRED) that lets you write models with analytical solutions.

Generating input data sets for mrgsolve

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…

Mixture model example

In this post, we’ll look at how you can code up a mixture model in mrgsolve.

A Complete Example

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…

Reproducible results with set.seed

This post demonstrates that random simulation outputs can be made reproducible by using set.seed().

Generate MAP Bayes Parameter Estimates

This tutorial illustrates now to do MAP Bayes estimation with mrgsolve.

MAP Bayes example

This is a shortened version of map_bayes.html, showing only the estimation step.

Work with event objects

event objects are data.frame-like data structures that allow you to quickly and flexibly include dosing interventions into your simulations.

Set initial conditions

initial conditions

There are several ways to set initial conditions in mrgsolve. Find out how this can work to your advantage when planning your simulations.