doubleml-for-pyDoubleML - Double Machine Learning in Python
Stars: ✭ 129 (+122.41%)
causeinferMachine learning based causal inference/uplift in Python
Stars: ✭ 45 (-22.41%)
CausalInferenceIntroCausal 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
Stars: ✭ 207 (+256.9%)
cfml toolsMy 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
Stars: ✭ 24 (-58.62%)
cfvqa[CVPR 2021] Counterfactual VQA: A Cause-Effect Look at Language Bias
Stars: ✭ 96 (+65.52%)
Probability TheoryA quick introduction to all most important concepts of Probability Theory, only freshman level of mathematics needed as prerequisite.
Stars: ✭ 25 (-56.9%)
grmpyPython package for the simulation and estimation of generalized Roy model
Stars: ✭ 14 (-75.86%)
RECCONThis repository contains the dataset and the PyTorch implementations of the models from the paper Recognizing Emotion Cause in Conversations.
Stars: ✭ 126 (+117.24%)
ScPoEconometricsUndergraduate textbook for Econometrics with R
Stars: ✭ 100 (+72.41%)
drtmleNonparametric estimators of the average treatment effect with doubly-robust confidence intervals and hypothesis tests
Stars: ✭ 14 (-75.86%)
FixedEffectjlrR interface for Fixed Effect Models
Stars: ✭ 20 (-65.52%)
Computational-EconomicsAlgorithmic game theory, recursive macroeconomics, machine learning for econometrics
Stars: ✭ 35 (-39.66%)
Diebold-Mariano-TestThis 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).
Stars: ✭ 70 (+20.69%)
RobynRobyn 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…
Stars: ✭ 433 (+646.55%)
econowcastExperimental tools (R) for Big Data econometrics nowcasting and early estimates
Stars: ✭ 26 (-55.17%)
causal-mlMust-read papers and resources related to causal inference and machine (deep) learning
Stars: ✭ 387 (+567.24%)
ARCHModels.jlA Julia package for estimating ARMA-GARCH models.
Stars: ✭ 63 (+8.62%)
CozCoz: Causal Profiling
Stars: ✭ 2,719 (+4587.93%)
PgmpyPython Library for learning (Structure and Parameter) and inference (Probabilistic and Causal) in Bayesian Networks.
Stars: ✭ 1,942 (+3248.28%)
FixedEffectModelFixedeffectmodel: panel data modeling in Python
Stars: ✭ 47 (-18.97%)
DowhyDoWhy 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.
Stars: ✭ 3,480 (+5900%)
causaldagPython package for the creation, manipulation, and learning of Causal DAGs
Stars: ✭ 82 (+41.38%)
mlr3tuningHyperparameter optimization package of the mlr3 ecosystem
Stars: ✭ 44 (-24.14%)
causalnlpCausalNLP is a practical toolkit for causal inference with text as treatment, outcome, or "controlled-for" variable.
Stars: ✭ 98 (+68.97%)
bacondecompBacon-Goodman decomposition for differences-in-differences with variation in treatment timing.
Stars: ✭ 36 (-37.93%)
tlverse-handbook🎯 📕 Targeted Learning in R: A Causal Data Science Handbook
Stars: ✭ 50 (-13.79%)
CausalityTools.jlAlgorithms for causal inference and the detection of dynamical coupling from time series, and for approximation of the transfer operator and invariant measures.
Stars: ✭ 45 (-22.41%)
Econ5121AEcon5121A@CUHK. This is an open-source writing project.
Stars: ✭ 56 (-3.45%)
Python-for-EpidemiologistsTutorial in Python targeted at Epidemiologists. Will discuss the basics of analysis in Python 3
Stars: ✭ 107 (+84.48%)
StatsmodelsStatsmodels: statistical modeling and econometrics in Python
Stars: ✭ 6,935 (+11856.9%)
policytreePolicy learning via doubly robust empirical welfare maximization over trees
Stars: ✭ 59 (+1.72%)
NNSNonlinear Nonparametric Statistics
Stars: ✭ 26 (-55.17%)
Awesome-Neural-LogicAwesome 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。
Stars: ✭ 106 (+82.76%)
awesome-quant-papersThis repository hosts my reading notes for academic papers.
Stars: ✭ 28 (-51.72%)
mlr3spatiotempcvSpatiotemporal resampling methods for mlr3
Stars: ✭ 43 (-25.86%)
hdfeNo description or website provided.
Stars: ✭ 22 (-62.07%)
Econ-Data-ScienceArticles/ Journals and Videos related to Economics📈 and Data Science 📊
Stars: ✭ 102 (+75.86%)
SMC.jlSequential Monte Carlo algorithm for approximation of posterior distributions.
Stars: ✭ 53 (-8.62%)
SINCausal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
Stars: ✭ 32 (-44.83%)
econ5170Econ5170@CUHK: Computational Methods in Economics (2020 Spring).
Stars: ✭ 127 (+118.97%)
cibookex-rCausal Inference: What If. R and Stata code for Exercises
Stars: ✭ 54 (-6.9%)
CausalmlUplift modeling and causal inference with machine learning algorithms
Stars: ✭ 2,499 (+4208.62%)
perfect match➕➕ Perfect Match is a simple method for learning representations for counterfactual inference with neural networks.
Stars: ✭ 100 (+72.41%)
pcalg-pyImplement PC algorithm in Python | PC 算法的 Python 实现
Stars: ✭ 52 (-10.34%)
Causal Reading GroupWe 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.
Stars: ✭ 339 (+484.48%)
cobaltCovariate Balance Tables and Plots - An R package for assessing covariate balance
Stars: ✭ 52 (-10.34%)
econtoolsEconometrics and data manipulation functions.
Stars: ✭ 96 (+65.52%)
CIKM18-LCVACode for CIKM'18 paper, Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects.
Stars: ✭ 13 (-77.59%)
priceREconomics and Pricing in R
Stars: ✭ 32 (-44.83%)
drnet💉📈 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.
Stars: ✭ 48 (-17.24%)
BeaData.jlA Julia interface for retrieving data from the Bureau of Economic Analysis (BEA).
Stars: ✭ 17 (-70.69%)
causal-learnCausal Discovery for Python. Translation and extension of the Tetrad Java code.
Stars: ✭ 428 (+637.93%)
gravityR package that provides estimation methods for Gravity Models
Stars: ✭ 24 (-58.62%)
hayashirR Companion to the textbook "Econometrics" by Fumio Hayashi
Stars: ✭ 29 (-50%)