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Calibration and simulation of state-dependent Hawkes processes.

Project description

The mpoints package

The mpoints package is a machine learning tool that implements the class of state-dependent Hawkes processes. Its key features include both simulation and estimation (statistical inference). It also contains a module with specialised plotting services.

State-dependent Hawkes processes belong to the class of hybrid marked point processes, a class that models the arrival in time of random events and their interaction with the state of a system.

We strongly recommend to first read the tutorial. It contains an introduction to this statistical model and illustrates the main services offered by the mpoints package.

For additional mathematical details, please consult the documentation and the references.


The package can be easily installed via pip, a popular package management system for Python. In the terminal, simply enter the following command.

pip install mpoints

If you are using virtual environments (with conda), make sure that you install the package in the intended environment.

Note: when installing mpoints on Windows, you may be prompted to install Visual C++ Build Tools if this is not already installed.

Build from source

Build the wheel using setuptools.

pip install -q build
python -m build

Install in development mode

If you are contributing to mpionts, you might want to install it in development mode. See development-mode

pip install --upgrade --force-reinstall --editable <path-to-mpoints-root>

Project details

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Source Distribution

mpoints-1.0.0.tar.gz (146.5 kB view hashes)

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