LeihuaYe / Causal-Inference-Using-Quasi-Experimental-MethodsLinks
Causal Inference Using Quasi-Experimental Methods
☆20Updated 5 years ago
Alternatives and similar repositories for Causal-Inference-Using-Quasi-Experimental-Methods
Users that are interested in Causal-Inference-Using-Quasi-Experimental-Methods are comparing it to the libraries listed below
Sorting:
- python app for doing personalized causal medicine using the methods invented by Judea Pearl et al.☆25Updated 2 years ago
- Code for blog posts.☆20Updated 2 years ago
- Epidemiology analysis package☆151Updated 2 years ago
- Source code for the paper "Causal Modeling of Twitter Activity during COVID-19". Computation, 2020.☆10Updated 2 years ago
- Repo for PyData 2019 Tutorial - New Trends in Estimation and Inference☆26Updated 6 years ago
- A full example for causal inference on real-world retail data, for elasticity estimation☆52Updated 4 years ago
- Quick cheat sheet to time series models using NYC Taxi Data☆17Updated 6 years ago
- 🪜 Bayesian Hierarchical Models at Scale☆51Updated 4 years ago
- Machine Learning models using a Bayesian approach and often PyMC3☆25Updated 5 years ago
- Implementation of algorithms from the paper "Globally-Consistent Rule-Based Summary-Explanations for Machine Learning Models: Application…☆25Updated 3 years ago
- A set of decks and notebooks with exercises for use in a hands-on causal inference tutorial session☆32Updated 3 years ago
- Pre-Modelling Analysis of the data, by doing various exploratory data analysis and Statistical Test.☆51Updated 2 years ago
- Data for and description of the ACIC 2023 data competition☆32Updated 2 years ago
- Handbook of Graphs and Networks in People Analytics☆123Updated last year
- ☆94Updated 8 years ago
- causaleffect: R package for identifying causal effects.☆37Updated 4 months ago
- A package for Safe Anytime Valid Inference☆26Updated last year
- Machine learning based causal inference/uplift in Python☆62Updated 2 weeks ago
- causal-falsify: A Python library with algorithms for falsifying unconfoundedness assumption in a composite dataset from multiple sources.☆36Updated 2 weeks ago
- ☆13Updated 3 years ago
- A method for estimating causal effects in time-series data. Uses available data to automatically find natural experiments for identifying…☆17Updated 6 years ago
- This repo aims to share the core algorithms used in the paper, "Global labor flow network reveals the hierarchical organization and dynam…☆30Updated 6 years ago
- R code for ''Bayesian method for causal inference in spatially-correlated multivariate time series''☆45Updated 5 years ago
- Educational resources☆105Updated 4 years ago
- This repository includes all the data analyses I carry out for my general exams reading, Spring 2015☆64Updated 10 years ago
- Tutorial in randomization inference, experimental design and analysis, and experiments in networks.☆30Updated 9 years ago
- Variable importance through targeted causal inference, with Alan Hubbard☆59Updated 3 months ago
- Minimax Estimation of Conditional Moment Models☆32Updated 2 years ago
- This is a read-only mirror of the CRAN R package repository. bsts — Bayesian Structural Time Series☆34Updated 5 months ago
- A Python Package providing two algorithms, DAME and FLAME, for fast and interpretable treatment-control matches of categorical data☆62Updated 6 months ago