causalsim
Simulation-Ready Causal Data Generating Processes
Construct, simulate, and evaluate causal data generating processes (DGPs) with known ground truth. Designed for benchmarking causal estimators, studying confounding and treatment-effect heterogeneity, and building reproducible teaching examples. Covariate roles (confounder, effect modifier, noise) and heterogeneous treatment effects are first-class concepts in the API, and estimator performance is summarised with bias, root mean squared error, confidence-interval coverage, and power.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | causalsim_0.1.0.tar.gz |
125.3 KiB |
0.1.0 |
rolling linux/noble R-4.5 | causalsim_0.1.0.tar.gz |
125.2 KiB |
0.1.0 |
rolling source/ R- | causalsim_0.1.0.tar.gz |
65.2 KiB |
0.1.0 |
latest linux/jammy R-4.5 | causalsim_0.1.0.tar.gz |
125.3 KiB |
0.1.0 |
latest linux/noble R-4.5 | causalsim_0.1.0.tar.gz |
125.2 KiB |
0.1.0 |
latest source/ R- | causalsim_0.1.0.tar.gz |
65.2 KiB |
0.1.0 |
2026-04-23 source/ R- | causalsim_0.1.0.tar.gz |
0 B |