tfm000/sklarpy
Copula fitting in Python.
This helps quantitative analysts and researchers understand the relationships between multiple variables in their data, even when those relationships are complex and non-linear. You provide raw numerical data for several processes or assets, and it outputs a statistical model (a 'copula') that describes how these variables move together, along with visualizations. This is for professionals like risk managers, actuaries, and financial modelers who need to characterize and simulate dependencies.
No commits in the last 6 months. Available on PyPI.
Use this if you need to model the joint behavior of several random variables without assuming they follow a simple normal distribution, especially in fields like finance or insurance.
Not ideal if you are looking for simple linear regression or basic correlation analysis, as this tool focuses on advanced, non-linear dependency modeling.
Stars
13
Forks
3
Language
Python
License
MIT
Category
Last pushed
Dec 04, 2023
Commits (30d)
0
Dependencies
7
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