Estimation of average treatment effects (ATE) of point interventions on time-to-event outcomes with K competing risks (K can be 1). The method uses propensity scores and inverse probability weighting for emulation of baseline randomization, which is described in Charpignon et al. (2022) <doi:10.1038/s41467-022-35157-w>.

Example data sets to run the example
    problems from causal inference textbooks. Currently, contains data
    sets for Huntington-Klein, Nick (2021 and 2025) "The Effect" <https://theeffectbook.net>, first and second edition,
    Cunningham, Scott (2021 and 2025, ISBN-13: 978-0-300-25168-5) "Causal Inference: The Mixtape", 
    and Hernán, Miguel and James Robins (2020) "Causal Inference: What If" 
    <https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/>.

Implements Le Cam deficiency theory for causal inference,
    as described in Akdemir (2026) <doi:10.5281/zenodo.18367347>. Provides
    theorem-backed bounds together with computable proxy diagnostics for
    information loss from confounding, selection bias, and distributional
    shift. Supports continuous, binary, count, survival, and competing risks
    outcomes. Key features include propensity-score total-variation deficiency
    proxies, negative control diagnostics, policy regret bounds, and
    sensitivity analysis via confounding frontiers.

Tools for causal structure learning from observational data, with emphasis on temporally
    ordered variables. The package implements the Temporal Peter–Clark (TPC) algorithm
    (Petersen, Osler & Ekstrøm, 2021; <doi:10.1093/aje/kwab087>), the Temporal Greedy
    Equivalence Search (TGES) algorithm (Larsen, Ekstrøm & Petersen, 2025; <doi:10.48550/arXiv.2502.06232>)
    and Temporal Fast Causal Inference (TFCI). It provides a unified framework for specifying background
    knowledge, which can be incorporated into the implemented algorithms from the R packages 'bnlearn'
    (Scutari, 2010; <doi:10.18637/jss.v035.i03>) and 'pcalg' (Kalish et al., 2012; <doi:10.18637/jss.v047.i11>),
    as well as the Java library 'Tetrad' (Scheines et al., 1998; <doi:10.1207/s15327906mbr3301_3>).
    The package further includes utilities for visualization, comparison, and evaluation of graph
    structures, facilitating performance evaluation and methodological studies.