64 Open source projects that are alternatives of or similar to SyntheticControlMethods

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

[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias

Must-read papers and resources related to causal inference and machine (deep) learning

DoubleML - Double Machine Learning in Python

DoubleML - Double Machine Learning in R

Machine learning based causal inference/uplift in Python

Econ5121A@CUHK. This is an open-source writing project.

My collection of causal inference algorithms built on top of accessible, simple, out-of-the-box ML methods, aimed at being explainable and useful in the business context

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A Julia interface for retrieving data from the Bureau of Economic Analysis (BEA).

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Python Library for learning (Structure and Parameter) and inference (Probabilistic and Causal) in Bayesian Networks.

Articles/ Journals and Videos related to Economics📈 and Data Science 📊

🎯 📕 Targeted Learning in R: A Causal Data Science Handbook

R package that provides estimation methods for Gravity Models

Econometrics and data manipulation functions.

Fixedeffectmodel: panel data modeling in Python

Statsmodels: statistical modeling and econometrics in Python

Coz: Causal Profiling

Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)

Python package for the creation, manipulation, and learning of Causal DAGs

This repository hosts my reading notes for academic papers.

Tutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3

Implement PC algorithm in Python | PC 算法的 Python 实现

ARMA-GARCH

No description or website provided.

💉📈 Dose response networks (DRNets) are a method for learning to estimate individual dose-response curves for multiple parametric treatments from observational data using neural networks.

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

Sequential Monte Carlo algorithm for approximation of posterior distributions.

🎓 GSU MPA/MPP course on program evaluation and causal inference

Experimental tools (R) for Big Data econometrics nowcasting and early estimates

R interface for Fixed Effect Models

Bacon-Goodman decomposition for differences-in-differences with variation in treatment timing.

Anchore container analysis and scan provided as a GitHub Action

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Microeconometric estimation in Julia

Economics and Pricing in R

➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.

INTERCEPT / Policy as Code Static Analysis Auditing / SAST

Collection of notebooks about quantitative finance, with interactive python code.

Uplift modeling and causal inference with machine learning algorithms

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).

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

A quick introduction to all most important concepts of Probability Theory, only freshman level of mathematics needed as prerequisite.

Covariate Balance Tables and Plots - An R package for assessing covariate balance

R Companion to the textbook "Econometrics" by Fumio Hayashi

Code for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.

Robyn is an experimental, automated and open-sourced Marketing Mix Modeling (MMM) package from Facebook Marketing Science. It uses various machine learning techniques (Ridge regression with cross validation, multi-objective evolutionary algorithm for hyperparameter optimisation, gradient-based optimisation for budget allocation etc.) to define m…

Causal Discovery for Python. Translation and extension of the Tetrad Java code.

We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.

Undergraduate textbook for Econometrics with R

Causal Inference: What If. R and Stata code for Exercises

Rode facilitates Automated Governance in your software supply chain. This repository contains the rode API which is the primary interface between the rode UI or rode Collectors and metadata storage in Grafeas. The rode API provides functions for metadata search and storage as well as policy creation and evaluation.

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This repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.

A Julia package for estimating ARMA-GARCH models.

Nonparametric estimators of the average treatment effect with doubly-robust confidence intervals and hypothesis tests

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Econ5170@CUHK: Computational Methods in Economics (2020 Spring).