Statsmodels: statistical modeling and econometrics in Python
Collection of notebooks about quantitative finance, with interactive python code.
#计算机科学#Lightning ⚡️ fast forecasting with statistical and econometric models.
#计算机科学#ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goal...
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
#计算机科学#2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
#计算机科学#A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function.
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
#时序数据库#Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX ...
LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
#学习与技能提升#This repository hosts the code behind the online book, Coding for Economists.
Causal Inference for the Brave and True的中文翻译版。全部代码基于Python,适用于计量经济学、量化社会学、策略评估等领域。英文版原作者:Matheus Facure
#时序数据库#Probabilistic Hierarchical forecasting 👑 with statistical and econometric methods.
#时序数据库#Advanced and Fast Data Transformation in R
#计算机科学#DoubleML - Double Machine Learning in Python
Replication of tables and figures from "Mostly Harmless Econometrics" in Stata, R, Python and Julia.
Visualise your CSV files in seconds without sending your data anywhere
📖An interactive companion to the well-received textbook 'Introduction to Econometrics' by Stock & Watson (2015)