Welcome to MeDIL’s documentation!
MeDIL is a Python package for causal factor analysis, using the measurement dependence inducing latent (MeDIL) causal model framework [MGW20].
The package is under active development—see the develop branch of the repository on GitLab or its Github mirror.
- Version:
1.1.0
- Date:
Oct 30, 2024
Installation:
You can install the package from PyPI with the command pip install medil.
Features:
scikit-learn-style API
estimation of sparse causal factor structure and loadings in the linear Gaussian setting or more generally using a deep generative model [MLAS23]
\(\ell_0\)-penalized maximum likelihood estimation (BIC score-based search) for minimum MeDIL causal graphs in the linear Gaussian setting, as well as nonparametric constraint-based search using distance covariance or xi correlation
random generation of and sampling from linear Gaussian causal factor models
exact search for minimum edge clique cover (ECC) [GGfN09] as well as polynomial time heuristic using the one-pure-child assumption [MLAS23]