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FPScausal: Functional Propensity Score for Causal Inference
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.
Package details |
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| Author | Nicole Fontana [aut, cre], Simone Ciardulli [aut] |
| Maintainer | Nicole Fontana <nicole.fontana@polimi.it> |
| License | MIT + file LICENSE |
| Version | 0.1.0 |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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