transitionMatrix is a Python powered library for the statistical analysis and visualization of state transition phenomena. It can be used to analyze any dataset that captures timestamped transitions in a discrete state space. Use cases include credit rating transitions, system state event logs etc.
You can use transitionMatrix to
- Estimate transition matrices from historical event data using a variety of estimators
- Visualize event data and transition matrices
- Manipulate transition matrices (generators, comparisons etc.)
- Provide standardized data sets for testing
- Model transitions using threshold processes
- Map credit ratings using mapping tables between popularly used rating systems
- Author: Open Risk
- License: Apache 2.0
- Code Documentation: Read The Docs
- Mathematical Documentation: Open Risk Manual
- Development website: Github
- General Discussions: Gitter Lobby
- Package Specific Chat: Gitter Project
NB: transitionMatrix is still in active development. If you encounter issues please raise them in our github repository
- The Open Risk Academy has free courses demonstrating the use of the library. The current list is:
- Commercial Support for transitionMatrix is provided as part of OpenCPM
The code documentation includes a large number of examples, jupyter notebooks and more.
Plotting individual transition trajectories
Sampling transition data
Estimation of transition matrices using cohort methods
Estimation of transition matrices using duration methods
Visualization of a transition matrix
Visualization using a Logarithmic Sankey diagram
Generating stochastic process transition thresholds
Stressing Transition Matrices
Computation and Visualization of Credit Curves
Working with credit states
