tick: a Python library for statistical learning, with an emphasis on Hawkes processes and time-dependent models.

*(English)*Zbl 06982970Summary: This paper introduces tick, is a statistical learning library for Python 3, with a particular emphasis on time-dependent models, such as point processes, tools for generalized linear models and survival analysis. The core of the library provides model computational classes, solvers and proximal operators for regularization. It relies on a C++ implementation and state-of-the-art optimization algorithms to provide very fast computations in a single node multi-core setting. Source code and documentation can be downloaded from https://github.com/X-DataInitiative/tick.

##### MSC:

62-04 | Software, source code, etc. for problems pertaining to statistics |

62J12 | Generalized linear models (logistic models) |

62N05 | Reliability and life testing |

60G55 | Point processes (e.g., Poisson, Cox, Hawkes processes) |

68T05 | Learning and adaptive systems in artificial intelligence |

90-04 | Software, source code, etc. for problems pertaining to operations research and mathematical programming |

##### Keywords:

learning; Python; Hawkes processes; optimization; generalized linear models; point process; survival analysis
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\textit{E. Bacry} et al., J. Mach. Learn. Res. 18, Paper No. 214, 5 p. (2018; Zbl 06982970)

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##### References:

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