Causal inference

• Overview
  • Causal inference in statistics:An overview (2009) Judea Pearl
  • An Introduction to Causal Inference (2010) Judea Pearl
  • Causality and statistical learning (2011) Andrew Gelman
  • Causal discovery and inference: concepts and recent methodological advances (2016) Peter Spirtes, Kun Zhang
  • A Survey of Learning Causality with Data: Problems and Methods (2018) Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu
  • Statistical Tools for Causal Inference (2020) The SKY Community
  • The fundamental problem of causal inference (Wiki)

Potential Outcomes

• On the application of probability theory to agricultural experiments (1923) Jerzy Neyman
• Estimating causal effects of treatments in randomized and nonrandomized studies (1974) Donald B. Rubin
• Causal Inference Using Potential Outcomes:Design, Modeling, Decisions (2005) Donald B. Rubin

Structural Causal Models

Causal Discovery

• PC Peter-Clark Algorithm
  • Copula PC Algorithm for Causal Discoveryfrom Mixed Data (2016) Ruifei Cui, Perry Groot, Tom Heskes
• FCI Fast Causal Inference
  • Causal Inference in the Presence of Latent Variables and Selection Bias (1995) Peter Spirtes, Christopher Meek, Thomas Richardson
  • Search for Additive Nonlinear TimeSeries Causal Models (2008) Tianjiao Chu, Clark Glymour
• GES Greedy Equivalence Search
  • Optimal Structure Identification With Greedy Search (2002) David Maxwell Chickering
• FCM Functional Causal Models
• ANM Additive Noise Models
  • Causal discovery of linear acyclic models with arbitrary distributions (2008) Patrik O. Hoyer, Aapo Hyvarinen, Richard Scheines, Peter Spirtes, Joseph Ramsey, Gustavo Lacerda, Shohei Shimizu
  • Nonlinear causal discovery with additive noise models (2009) Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, Jonas Peters, Bernhard Schölkop
• Granger causality
  • Investigating Causal Relations by Econometric Models and Cross-spectral Methods (1969) C. W. J. Granger
  • Aalyzing multiple nonlinear time series with extended Granger causality (2004) Yonghong Chena, Govindan Rangarajanc, Jianfeng Fenge, Mingzhou Ding
  • Large-scale nonlinear Granger causality: A data-driven, multivariateapproach to recovering directed networks from short time-series data (2020) Axel Wismuller, Adora M. DSouza, Anas Z. Abidin

Software

• Python
  • tigramite (Homepage)