The goal of mipdeval is to make it easy to evaluate predictive performance of PK/PD models in historical datasets, in the context of model-informed precision dosing (specifically Bayesian updating)
Install the development version from GitHub with:
# install.packages("pak")
pak::pak("InsightRX/mipdeval")run_eval(
model = model,
data = data,
... # additional arguments, see docs
)
We welcome input from the community:
-
If you think you have encountered a bug, please submit an issue on the GitHub page. Please include a reproducible example of the unexpected behavior.
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Please open a pull request if you have a fix or updates that would improve the package. If you’re not sure if your proposedchanges are useful or within scope of the package, feel free to contact one of the authors of this package.
The functionality in this R package is provided “as is”. While its authors adhere to software development best practices, the software may still contain unintended errors.
InsightRX Inc. and the authors of this package can not be held liable for any damages resulting from any use of this software. By the use of this software package, the user waives all warranties, expressed or implied, including any warranties to the accuracy, quality or suitability of InsightRX for any particular purpose, either medical or non-medical.
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