@article{kook2024algorithm,title={{Algorithm-agnostic significance testing in supervised learning with multimodal data}},author={Kook, Lucas and Lundborg, Anton Rask},year={2024},doi={10.48550/arXiv.2402.14416},eprint={2402.14416},archiveprefix={arXiv},primaryclass={stat.AP}}
2023
arXiv
Perturbation-based Effect Measures for Compositional Data
@misc{lundborg2023perturbationbased,doi={10.48550/arXiv.2311.18501},author={Lundborg, Anton Rask and Pfister, Niklas},title={Perturbation-based Effect Measures for Compositional Data},year={2023},eprint={2311.18501},archiveprefix={arXiv},primaryclass={stat.ME}}
arXiv
Model-based causal feature selection for general response types
@misc{kook2023model,doi={10.48550/ARXIV.2309.12833},author={Kook, Lucas and Saengkyongam, Sorawit and Lundborg, Anton Rask and Hothorn, Torsten and Peters, Jonas},keywords={Methodology (stat.ME), Statistics Theory (math.ST), Machine Learning (stat.ML)},title={Model-based causal feature selection for general response types},publisher={arXiv},year={2023},copyright={Creative Commons Attribution 4.0 International},}
2022
arXiv
The Projected Covariance Measure for assumption-lean variable significance testing
@misc{lundborg2022projected,doi={10.48550/ARXIV.2211.02039},author={Lundborg, Anton Rask and Kim, Ilmun and Shah, Rajen D. and Samworth, Richard J.},keywords={Statistics Theory (math.ST), Methodology (stat.ME), Machine Learning (stat.ML), FOS: Mathematics, FOS: Mathematics, FOS: Computer and information sciences, FOS: Computer and information sciences, 62G10},title={The Projected Covariance Measure for assumption-lean variable significance testing},publisher={arXiv},year={2022},copyright={Creative Commons Attribution 4.0 International},}
@misc{guo2022confounder,doi={10.48550/ARXIV.2208.13871},author={Guo, F. Richard and Lundborg, Anton Rask and Zhao, Qingyuan},keywords={Methodology (stat.ME), Statistics Theory (math.ST), FOS: Computer and information sciences, FOS: Computer and information sciences, FOS: Mathematics, FOS: Mathematics},title={Confounder Selection: Objectives and Approaches},publisher={arXiv},year={2022},copyright={Creative Commons Attribution 4.0 International},}
Statistical publications
2022
JRSSB
Conditional independence testing in Hilbert spaces with applications to functional data analysis
@article{lundborg2022conditional,title={Conditional independence testing in Hilbert spaces with applications to functional data analysis},author={Lundborg, Anton Rask and Shah, Rajen D. and Peters, Jonas},journal={Journal of the Royal Statistical Society: Series B (Statistical Methodology)},volume={84},number={5},pages={1821-1850},keywords={functional graphical model, function-on-function regression, significance testing, truncated functional linear model, uniform type I error control},doi={10.1111/rssb.12544},year={2022},}
Applied publications
2024
BMJ
Towards a better understanding of real-world home-visiting programs: a large-scale effectiveness study of parenting mechanisms in Brazil
Morgan Rebecca Healy, Eduardo Viegas Silva, Anton Rask Lundborg, Fernando Pires Hartwig, Tiago Neuenfeld Munhoz, Adriane Xavier Arteche, Paul G Ramchandani, and Joseph Murray
@article{healy2024towards,author={Healy, Morgan Rebecca and da Silva, Eduardo Viegas and Lundborg, Anton Rask and Hartwig, Fernando Pires and Munhoz, Tiago Neuenfeld and Arteche, Adriane Xavier and Ramchandani, Paul G and Murray, Joseph},title={Towards a better understanding of real-world home-visiting programs: a large-scale effectiveness study of parenting mechanisms in Brazil},volume={9},number={2},elocation-id={e013787},year={2024},doi={10.1136/bmjgh-2023-013787},publisher={BMJ Specialist Journals},url={https://gh.bmj.com/content/9/2/e013787},journal={BMJ Global Health},}
Software packages
R code for ghcm available on CRAN. Source and bug report on GitHub.