Multiresolution categorical regression for interpretable cell‐type annotation
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DOI: 10.1111/biom.13926
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References listed on IDEAS
- Nibbering, Didier & Hastie, Trevor J., 2022. "Multiclass-penalized logistic regression," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
- Xiaohan Yan & Jacob Bien, 2021. "Rare Feature Selection in High Dimensions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(534), pages 887-900, April.
- Aaron J. Molstad & Adam J. Rothman, 2023. "A Likelihood-Based Approach for Multivariate Categorical Response Regression in High Dimensions," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 118(542), pages 1402-1414, April.
- Bianca Dumitrascu & Soledad Villar & Dustin G. Mixon & Barbara E. Engelhardt, 2021. "Optimal marker gene selection for cell type discrimination in single cell analyses," Nature Communications, Nature, vol. 12(1), pages 1-8, December.
- Ming Yuan & Yi Lin, 2006. "Model selection and estimation in regression with grouped variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 68(1), pages 49-67, February.
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