Welcome to APT-MCMC’s documentation!¶

In order to get started, going through the Requirements is recommended to ensure your system has the correct libraries to run APT-MCMC simulations. After that, consult the Tutorial for a Quick-Start guide on parameter fitting, which should covers parameter fitting to a 2-state, 2-parameter ODE system. This should cover the majority of use-cases.

For advanced fitting requirements, consult documentation regarding the APT-MCMC object that best pertains to your requirements. In a worst case scenario, APT-MCMC can be used to generate the bulk (and very repetative) aspects of C++ simulation code, which may then be edited directly.

Supports:

Automatic C++` generation if the user can specify a model within the confines of APTmodel
Unknown initial conditions are supported and can be parameters.
A data timeshift can be a parameter. This is in the event of data being collected at some time after the true beginning of a dynamical system. A typical use case would be hospital data, where data is relative to enrollment rather than disease time zero.
Infusions (ramp, bolus, zero-order-hold, or any combination thereof) are fully supported, but magnitudes, times, and durations MUST be known. They cannot be parameters.

Note

Advanced use case: Infusions can be combined with a timeshift as long as it is known when the infusion occured, relative to the start of data collection.