aadya940/chainopy
ChainoPy: A Python Library for Discrete Time Markov Chain based stochastic analysis
This helps data scientists and quantitative analysts perform advanced stochastic analysis on time-series data. You input sequential data, such as financial market movements or weather patterns, and it outputs models that predict future states or identify hidden patterns. It’s ideal for anyone looking to understand and forecast systems that transition between distinct states over time.
No commits in the last 6 months. Available on PyPI.
Use this if you need to build predictive models for systems where the next state depends only on the current state, like stock prices, weather forecasting, or customer behavior.
Not ideal if your data doesn't exhibit clear state transitions or if you need models for purely continuous, non-sequential data without underlying regimes.
Stars
22
Forks
1
Language
Jupyter Notebook
License
BSD-2-Clause
Category
Last pushed
Aug 16, 2024
Commits (30d)
0
Dependencies
8
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