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nlmixr2lib
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<!-- badges: start --> [](https://github.com/nlmixr2/nlmixr2lib/actions/workflows/R-CMD-check.yaml) [](https://app.codecov.io/gh/nlmixr2/nlmixr2lib) [](https://CRAN.R-project.org/package=nlmixr2lib) <!-- badges: end --> # nlmixr2lib This is a model library for `nlmixr2`. The package allows a few ways to interact with the model library: ```r # See all available models modellib() # Load the "PK_1cmt" model modellib(name="PK_1cmt") # Switch residual error to additive modellib(name="PK_1cmt", reserr = "addSd") # Add inter-individual variability on ka and v and switch residual error to # additive and proportional modellib(name="PK_1cmt", eta = c("lka", "lv"), reserr = c("addSd", "propSd")) ``` # Modifying models by piping You may also modify any model from the library (or your own models) with a piping interface. The code below adds inter-individual variability on ka and v and then switches residual error to additive and proportional. ```r modellib(name="PK_1cmt") |> addEta(c("lka", "lv") |> addResErr(c("addSd", "propSd")) ``` # Possible extensions The `modellib` function is set-up in way that it can be easily extended and used in other applications. A possible extension could be implementation in a shiny app. An app can be created to easily add new models to the model library database (curated?), and directly make these models available for other users. I believe there can be added value in having a base model library that can be easily extended by the community this way.
