Package: FPScausal
Type: Package
Title: Functional Propensity Score for Causal Inference
Version: 0.1.1
Authors@R: c(
    person("Nicole", "Fontana", email = "nicole.fontana@polimi.it",
           role = c("aut", "cre")),
    person("Simone", "Ciardulli", email = "simone.ciardulli@mail.polimi.it",
           role = "aut"),
    person("Simone", "Vantini", role = "ths"),
    person("Francesca", "Ieva", role = "ths"))
Description: Implements functional propensity score (FPS) weighting for
        causal inference with functional treatments. The method
        estimates weights that balance observed confounders by removing
        their dependence on the functional treatment and uses a dual
        formulation of the weighting problem for efficient
        unconstrained optimization. The framework supports scalar,
        binary, and functional outcomes, as well as functional
        covariates, and can be used to estimate marginal causal effects
        in settings with time-varying exposures. The methodology
        follows Ciardulli, S., Fontana, N., Vantini, S., and Ieva, F.
        (2026) "Generalized propensity score weighting for functional
        causal inference framework" <doi:10.48550/arXiv.2608.03200>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: fda (>= 6.0.0), ggplot2 (>= 3.4.0), tidyr (>= 1.2.0), MASS (>=
        7.3-0), wCorr, patchwork (>= 1.1.0), progress (>= 1.2.0),
        stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 7.3.1
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-09-22 08:59:26 UTC; root
Author: Nicole Fontana [aut, cre], Simone Ciardulli [aut], Simone
        Vantini [ths], Francesca Ieva [ths]
Maintainer: Nicole Fontana <nicole.fontana@polimi.it>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-08-23 10:20:02 UTC
RemoteUrl: https://github.com/cran/FPScausal
RemoteRef: HEAD
RemoteSha: 2ae0642a6d7955d1108f2a158ae922157388f398