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FPScausal  

Functional Propensity Score for Causal Inference
View on CRAN: Click here


Download and install FPScausal package within the R console
Install from CRAN:
install.packages("FPScausal")

Install from Github:
library("remotes")
install_github("cran/FPScausal")

Install by package version:
library("remotes")
install_version("FPScausal", "0.1.1")



Attach the package and use:
library("FPScausal")
Maintained by
Nicole Fontana
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-08-09
Latest Update: 2026-08-09
Description:
Implements functional propensity score (FPS) weighting for causal inference with functional treatments. Weights are estimated by maximising the empirical likelihood subject to covariate-balancing constraints and solving the resulting dual problem via the BFGS quasi-Newton algorithm, following Ciardulli, S. and Fontana, N. (2026). The package supports scalar, binary, and functional outcomes, as well as functional covariates.
How to cite:
Nicole Fontana (2026). FPScausal: Functional Propensity Score for Causal Inference. R package version 0.1.1, https://cran.r-project.org/web/packages/FPScausal. Accessed 03 Oct. 2026.
Previous versions and publish date:
0.1.0 (2026-08-09 10:00), (2026-08-23 12:20)
Other packages that cited FPScausal R package
View FPScausal citation profile
Other R packages that FPScausal depends, imports, suggests or enhances
Complete documentation for FPScausal
Functions, R codes and Examples using the FPScausal R package
Full FPScausal package functions and examples
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