Robust regression with compositional covariates

DOI10.1016/j.csda.2021.107315OpenAlexW3185996219MaRDI QIDQ2242144

Christian L. Müller, A. M. Mishra

Publication date: 9 November 2021

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1909.04990

zbMATH Keywords

robustcompositional datasparsitymean shiftmicrobiome

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (4)

RobRegCC ⋮ Robust Multivariate Lasso Regression with Covariance Estimation ⋮ A review of compositional data analysis and recent advances ⋮ A decomposition method for Lasso problems with zero-sum constraint

Uses Software

• R
• robustbase
• UNLocBoX
• RobStatTM
• ConstrainedLasso

Cites Work

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• Imputation of missing values for compositional data using classical and robust methods
• Variable selection in regression with compositional covariates
• Log-Contrast Regression with Functional Compositional Predictors: Linking Preterm Infant's Gut Microbiome Trajectories to Neurobehavioral Outcome
• The Adaptive Lasso and Its Oracle Properties
• Regularization of case-specific parameters for robustness and efficiency
• Regression analysis for microbiome compositional data
• Primal-dual splitting algorithm for solving inclusions with mixtures of composite, Lipschitzian, and parallel-sum type monotone operators
• High breakdown-point and high efficiency robust estimates for regression
• Oracle inequalities and optimal inference under group sparsity
• Wavelet methods in statistics: some recent developments and their applications
• Kernel-penalized regression for analysis of microbiome data
• Thresholding-based iterative selection procedures for model selection and shrinkage
• Robust elastic net estimators for variable selection and identification of proteomic biomarkers
• Structured subcomposition selection in regression and its application to microbiome data analysis
• Proximal Splitting Methods in Signal Processing
• Confidence Intervals and Hypothesis Testing for High-Dimensional Regression
• Robust Lasso With Missing and Grossly Corrupted Observations
• Outlier Detection Using Nonconvex Penalized Regression
• Algorithms for Fitting the Constrained Lasso
• Regularization of Wavelet Approximations
• A Fast Procedure for Outlier Diagnostics in Large Regression Problems
• On the Convergence of the Iterative Shrinkage/Thresholding Algorithm With a Weakly Convex Penalty
• Robust Statistics
• An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
• Linear regression with compositional explanatory variables
• Log‐ratio lasso: Scalable, sparse estimation for log‐ratio models
• Regularization and Variable Selection Via the Elastic Net
• Selective factor extraction in high dimensions
• Robust reduced-rank regression
• On the finite-sample analysis of \(\Theta\)-estimators
• Convex analysis and monotone operator theory in Hilbert spaces

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