powerlaw-devs/powerlaw

Fitting power-law distributions to empirical data, according to the method of Clauset, Shalizi and Newman

Fit data to many distributions

distfit is a python library for probability density fitting.

Dependence-aware block-maxima inference for severity, persistence, and design-life levels.

Model manipulation and fitting library based on TensorFlow and optimised for simple and direct manipulation of probability density functions. Its main focus is on scalability, parallelisation and user friendly experience.

Extreme Value Analysis (EVA) in Python

A Python package for survival analysis. The most flexible survival analysis package available. SurPyval can work with arbitrary combinations of observed, censored, and truncated data. SurPyval can also fit distributions with 'offsets' with ease, for example the three parameter Weibull distribution.

Help to Fit of a Parametric Distribution to Non-Censored or Censored Data

Probabilistic reasoning and statistical analysis in TensorFlow