Robust regression estimation and variable selection when cellwise and casewise outliers are present
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Publication:5164433
DOI10.15672/hujms.734212zbMath1488.62113OpenAlexW3125293692MaRDI QIDQ5164433
Olcay Arslan, Onur Toka, Meral Çetin
Publication date: 11 November 2021
Published in: Hacettepe Journal of Mathematics and Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.15672/hujms.734212
Ridge regression; shrinkage estimators (Lasso) (62J07) Robustness and adaptive procedures (parametric inference) (62F35)
Uses Software
Cites Work
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- Multivariate Outliers and the O3 Plot
- Snipping for robust \(k\)-means clustering under component-wise contamination
- The shooting S-estimator for robust regression
- Weighted LAD-LASSO method for robust parameter estimation and variable selection in regression
- Robust estimation of multivariate location and scatter in the presence of cellwise and casewise contamination
- High breakdown-point and high efficiency robust estimates for regression
- An imputation method for categorical variables with application to nonlinear principal component analysis
- Sequential imputation for missing values
- Propagation of outliers in multivariate data
- Robust data imputation
- Multivariate location and scatter matrix estimation under cellwise and casewise contamination
- Robust regression estimation and inference in the presence of cellwise and casewise contamination
- Outlyingness: which variables contribute most?
- A generalized spatial sign covariance matrix
- Adaptive robust variable selection
- Penalized MM regression estimation withLγpenalty: a robust version of bridge regression
- Robust Statistics
- Robust Regression and Lasso
- Regularization and Variable Selection Via the Elastic Net
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
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