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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "IVDML" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'IVDML: Double Machine Learning with Instrumental Variables and Heterogeneity'
version: 1.0.0
doi: 10.32614/CRAN.package.IVDML
abstract: Instrumental variable (IV) estimators for homogeneous and heterogeneous
  treatment effects with efficient machine learning instruments. The estimators are
  based on double/debiased machine learning allowing for nonlinear and potentially
  high-dimensional control variables. Details can be found in Scheidegger, Guo and
  Bühlmann (2025) "Inference for heterogeneous treatment effects with efficient instruments
  and machine learning" <https://doi.org/10.48550/arXiv.2503.03530>.
authors:
- family-names: Scheidegger
  given-names: Cyrill
  email: cyrill.scheidegger@stat.math.ethz.ch
  orcid: https://orcid.org/0009-0005-2851-1384
repository: https://cyrillsch.r-universe.dev
repository-code: https://github.com/cyrillsch/IVDML
commit: e1ab9dfb30cceff70118c9f0297bbb2bc0f96856
url: https://github.com/cyrillsch/IVDML
contact:
- family-names: Scheidegger
  given-names: Cyrill
  email: cyrill.scheidegger@stat.math.ethz.ch
  orcid: https://orcid.org/0009-0005-2851-1384