Intro
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
- Manipulate transition matrices (generators, comparisons etc.)
- Visualize event data and transition matrices
- Provide standardized data sets for testing
- Model transitions using threshold processes
- Map credit ratings using mapping tables between popularly used rating systems
Key Information
- Author: Open Risk
- License: Apache 2.0
- Code Documentation: Read The Docs
- Mathematical Documentation: Open Risk Manual
- Development website: Github
- Project Chat: Open Risk Commons
NB: transitionMatrix is still in active development. If you encounter issues or have suggestions please raise them in our github repository or come discuss at our discourse server
Support and Training
- The Open Risk Academy has free courses demonstrating the use of the library. The current list is:
- Support for transitionMatrix and other open source libraries developed by Open Risk is available upon request
Examples
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
