Tick: a Python library for statistical learning, with a particular emphasis on time-dependent modelling
This provides a tool for researchers and practitioners in fields like survival analysis and time-series modeling, but it is incremental as it builds on existing optimization methods.
The authors introduced Tick, a Python library for statistical learning that focuses on time-dependent models like point processes, offering fast computations through C++ implementation and state-of-the-art optimization algorithms.
Tick is a statistical learning library for Python~3, with a particular emphasis on time-dependent models, such as point processes, and tools for generalized linear models and survival analysis. The core of the library is an optimization module providing model computational classes, solvers and proximal operators for regularization. tick 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