Higher-Order Influence Function Estimators for the Average Treatment Effect R package HOIF version 0.2.0 Implements Higher-Order Influence Function (HOIF) estimators of the Average Treatment Effect (ATE), following Robins et al. (2008) <doi:10.1214/193940307000000527>, Liu et al. (2017) <doi:10.48550/arXiv.1705.07577> and Liu and Li (2023) <doi:10.48550/arXiv.2302.08097>. Estimators of any order are supported, with optional covariate basis transformations (B-splines, Fourier) and optional K-fold sample splitting (cross-fitting) for improved finite-sample performance. The core higher-order U-statistics are computed exactly via the 'ustats' package, an R interface to the 'Python' package 'u-stats'; the underlying algorithm and its computational complexity are analyzed in Chen, Zhang and Liu (2025) <doi:10.48550/arXiv.2508.12627>. A pure R implementation (up to order 6) is also provided as a fallback that does not require 'Python'. Software Depends: R (>= 4.0.0) Imports: splines, corpcor, SMUT, ustats (>= 0.1.5) Suggests: MASS, testthat (>= 3.0.0), reticulate, knitr, rmarkdown Xingyu Chen <xingyuchen0714@sjtu.edu.cn> Comprehensive R Archive Network (CRAN) Xingyu Chen [aut, cre], Lin Liu [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=HOIF/LICENSE) 2026-06-24 application/tgz https://CRAN.R-project.org/package=HOIF doi:10.32614/CRAN.package.HOIF en-US