Statsmodels: statistical modeling and econometrics in Python
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Updated
Jun 27, 2024 - Python
Statsmodels: statistical modeling and econometrics in Python
Lightning ⚡️ fast forecasting with statistical and econometric models.
A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
DoubleML - Double Machine Learning in Python
CausalLift: Python package for causality-based Uplift Modeling in real-world business
An open source library for Fuzzy Time Series in Python
Applied Econometrics Library for Python
A Python package for causal inference using Synthetic Controls
Tools for financial economics. Curated wrapper over Python ecosystem. Source code for fecon235 Jupyter notebooks.
Vanilla option pricing and visualisation using Black-Scholes model in pure Python
Econometrics and data manipulation functions.
This Python function dm_test implements the Diebold-Mariano Test (1995) to statistically test forecast accuracy equivalence for 2 sets of predictions with modification suggested by Harvey et. al (1997).
ARMA-GARCH
difference-in-differences in Python
Python tools for regression discontinuity designs
Implements the Causal Forest algorithm formulated in Athey and Wager (2018).
Spatial econometric regression in Python
Machine learning based causal inference/uplift in Python
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