Double Machine Learning for Static Panel Models with Fixed Effects [R package xtdml version 0.1.9]

Annalivia Polselli

xtdml: Double Machine Learning for Static Panel Models with Fixed Effects

The 'xtdml' package implements partially linear panel regression (PLPR) models with high-dimensional confounding variables and an exogenous treatment variable within the double machine learning framework. The package is used to estimate the structural parameter (treatment effect) in static panel data models with fixed effects using the approaches established in Clarke and Polselli (2025) <doi:10.1093/ectj/utaf011>. 'xtdml' is built on the object-oriented package 'DoubleML' (Bach et al., 2024) <doi:10.18637/jss.v108.i03> using the 'mlr3' ecosystem.

Version: 0.1.9

Depends: R (≥ 3.5.0)

Imports: R6 (≥ 2.4.1), data.table (≥ 1.12.8), mlr3 (≥ 0.19.0), mlr3tuning (≥ 0.20.0), mlr3learners (≥ 0.3.0), mlr3misc (≥ 0.19.0), mvtnorm, utils, clusterGeneration, readstata13, magrittr, dplyr, stats, MLmetrics, checkmate

Suggests: rpart, mlr3pipelines, bbotk (≥ 1.6.0)

Published: 2025年11月12日

DOI: 10.32614/CRAN.package.xtdml

Author: Annalivia Polselli ORCID iD [aut, cre]

Maintainer: Annalivia Polselli <apolselli.econ at gmail.com>

License: GPL-2 | GPL-3

NeedsCompilation: no

Materials: README

CRAN checks: xtdml results

Documentation:

Reference manual: xtdml.html , xtdml.pdf

Downloads:

Package source: xtdml_0.1.9.tar.gz

Windows binaries: r-devel: xtdml_0.1.9.zip, r-release: xtdml_0.1.9.zip, r-oldrel: xtdml_0.1.9.zip

macOS binaries: r-release (arm64): xtdml_0.1.9.tgz, r-oldrel (arm64): xtdml_0.1.9.tgz, r-release (x86_64): xtdml_0.1.9.tgz, r-oldrel (x86_64): xtdml_0.1.9.tgz

Old sources: xtdml archive

Linking:

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