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        "author": "Maxime Morariu-Patrichi, Mikko Pakkanen",
        "author_email": "maximemorariu@me.com",
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        "description": "# The mpoints package\n\nThe `mpoints` package is a machine learning tool that implements the class of state-dependent Hawkes processes.\nIts key features include both simulation and estimation (statistical inference).\nIt also contains a module with specialised plotting services.\n\nState-dependent Hawkes processes belong to the class of hybrid marked point processes,\na class that models the arrival in time of random events and their interaction with the state of a system.\n\nWe strongly recommend to first read the [tutorial](https://mpoints.readthedocs.io/en/latest/tutorial.html).\nIt contains an introduction to this statistical model and illustrates the main services offered by the `mpoints` package.\n\nFor additional mathematical details, please consult the [documentation](https://mpoints.readthedocs.io) and the \n[references](https://mpoints.readthedocs.io/en/latest/references.html).\n\n## Installation\n\nThe package can be easily installed via `pip`, a popular package management system for Python. In the terminal, simply enter the following command.\n\n```\n    pip install mpoints\n```\nIf you are using virtual environments (with conda), make sure that you install the package in the intended environment.\n\nNote: when installing `mpoints` on Windows, you may be prompted to install Visual C++ Build Tools if this is not already installed.\n\n",
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