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Variable selection in regression with compositional covariates

Citations

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Cited by:

  1. Jacob Fiksel & Scott Zeger & Abhirup Datta, 2022. "A transformation‐free linear regression for compositional outcomes and predictors," Biometrics, The International Biometric Society, vol. 78(3), pages 974-987, September.
  2. Srinivasan, Arun & Xue, Lingzhou & Zhan, Xiang, 2023. "Identification of microbial features in multivariate regression under false discovery rate control," Computational Statistics & Data Analysis, Elsevier, vol. 181(C).
  3. Jordi Saperas-Riera & Glòria Mateu-Figueras & Josep Antoni Martín-Fernández, 2024. "L p -Norm for Compositional Data: Exploring the CoDa L 1 -Norm in Penalised Regression," Mathematics, MDPI, vol. 12(9), pages 1-16, May.
  4. Haixiang Zhang & Jun Chen & Zhigang Li & Lei Liu, 2021. "Testing for Mediation Effect with Application to Human Microbiome Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(2), pages 313-328, July.
  5. G. S. Monti & P. Filzmoser, 2022. "Robust logistic zero-sum regression for microbiome compositional data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 16(2), pages 301-324, June.
  6. Jeon, Jong-June & Kim, Yongdai & Won, Sungho & Choi, Hosik, 2020. "Primal path algorithm for compositional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 148(C).
  7. Zhigang Li & Katherine Lee & Margaret R. Karagas & Juliette C. Madan & Anne G. Hoen & A. James O’Malley & Hongzhe Li, 2018. "Conditional Regression Based on a Multivariate Zero-Inflated Logistic-Normal Model for Microbiome Relative Abundance Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 587-608, December.
  8. Cristofari, Andrea, 2023. "A decomposition method for lasso problems with zero-sum constraint," European Journal of Operational Research, Elsevier, vol. 306(1), pages 358-369.
  9. Lingjing Jiang & Niina Haiminen & Anna‐Paola Carrieri & Shi Huang & Yoshiki Vázquez‐Baeza & Laxmi Parida & Ho‐Cheol Kim & Austin D. Swafford & Rob Knight & Loki Natarajan, 2022. "Utilizing stability criteria in choosing feature selection methods yields reproducible results in microbiome data," Biometrics, The International Biometric Society, vol. 78(3), pages 1155-1167, September.
  10. Gen Li & Yan Li & Kun Chen, 2023. "It's all relative: Regression analysis with compositional predictors," Biometrics, The International Biometric Society, vol. 79(2), pages 1318-1329, June.
  11. Juan José Egozcue & Vera Pawlowsky-Glahn, 2019. "Compositional data: the sample space and its structure," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 599-638, September.
  12. Xiao Liu & Bao-Jin Wang & Luo Xu & Hong-Ling Tang & Guo-Qing Xu, 2017. "Selection of key sequence-based features for prediction of essential genes in 31 diverse bacterial species," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-13, March.
  13. Liangliang Zhang & Yushu Shi & Robert R. Jenq & Kim‐Anh Do & Christine B. Peterson, 2021. "Bayesian compositional regression with structured priors for microbiome feature selection," Biometrics, The International Biometric Society, vol. 77(3), pages 824-838, September.
  14. Zachary D Kurtz & Christian L Müller & Emily R Miraldi & Dan R Littman & Martin J Blaser & Richard A Bonneau, 2015. "Sparse and Compositionally Robust Inference of Microbial Ecological Networks," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-25, May.
  15. Zemin Zheng & Jinchi Lv & Wei Lin, 2021. "Nonsparse Learning with Latent Variables," Operations Research, INFORMS, vol. 69(1), pages 346-359, January.
  16. Huiwen Wang & Zhichao Wang & Shanshan Wang, 2021. "Sliced inverse regression method for multivariate compositional data modeling," Statistical Papers, Springer, vol. 62(1), pages 361-393, February.
  17. Arun Srinivasan & Lingzhou Xue & Xiang Zhan, 2021. "Compositional knockoff filter for high‐dimensional regression analysis of microbiome data," Biometrics, The International Biometric Society, vol. 77(3), pages 984-995, September.
  18. Sean M Devlin & Axel Martin & Irina Ostrovnaya, 2021. "Identifying prognostic pairwise relationships among bacterial species in microbiome studies," PLOS Computational Biology, Public Library of Science, vol. 17(11), pages 1-12, November.
  19. Rieser, Christopher & Filzmoser, Peter, 2023. "Extending compositional data analysis from a graph signal processing perspective," Journal of Multivariate Analysis, Elsevier, vol. 198(C).
  20. Jiarui Lu & Pixu Shi & Hongzhe Li, 2019. "Generalized linear models with linear constraints for microbiome compositional data," Biometrics, The International Biometric Society, vol. 75(1), pages 235-244, March.
  21. Jiajia Chen & Xiaoqin Zhang & Shengjia Li, 2017. "Multiple linear regression with compositional response and covariates," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(12), pages 2270-2285, September.
  22. Xiaofei Wu & Rongmei Liang & Hu Yang, 2022. "Penalized and constrained LAD estimation in fixed and high dimension," Statistical Papers, Springer, vol. 63(1), pages 53-95, February.
  23. Mishra, Aditya & Müller, Christian L., 2022. "Robust regression with compositional covariates," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
  24. Patrick L. Combettes & Christian L. Müller, 2021. "Regression Models for Compositional Data: General Log-Contrast Formulations, Proximal Optimization, and Microbiome Data Applications," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(2), pages 217-242, July.
  25. Licai Huang & Paul Little & Jeroen R. Huyghe & Qian Shi & Tabitha A. Harrison & Greg Yothers & Thomas J. George & Ulrike Peters & Andrew T. Chan & Polly A. Newcomb & Wei Sun, 2021. "A Statistical Method for Association Analysis of Cell Type Compositions," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 373-385, December.
  26. Yuan, Panxu & Jin, Changhan & Li, Gaorong, 2024. "FDR control for linear log-contrast models with high-dimensional compositional covariates," Computational Statistics & Data Analysis, Elsevier, vol. 197(C).
  27. Bingkai Wang & Brian S. Caffo & Xi Luo & Chin‐Fu Liu & Andreia V. Faria & Michael I. Miller & Yi Zhao & for the Alzheimer's Disease Neuroimaging Initiative*, 2022. "Regularized regression on compositional trees with application to MRI analysis," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 541-561, June.
  28. Enora Belz & Arthur Charpentier, 2019. "Aggregated Data and Compositional Variables: Methodological Note [Données Agrégées et Variables Compositionnelles : Note Méthodologique]," Working Papers hal-02097031, HAL.
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