Principal component regression for data containing outliers and missing elements
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Publication:961870
DOI10.1016/j.csda.2009.04.008zbMath1453.62193OpenAlexW3217316640MaRDI QIDQ961870
Publication date: 1 April 2010
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2009.04.008
Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Robustness and adaptive procedures (parametric inference) (62F35)
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Uses Software
Cites Work
- High breakdown estimators for principal components: the projection-pursuit approach revis\-ited
- Multivariate least-trimmed squares regression estimator
- The influence function of the Stahel-Donoho covariance estimator of smallest outlyingness
- Principal component analysis for data containing outliers and missing elements
- Robust principal component analysis for functional data. (With comments)
- The multivariate least-trimmed squares estimator
- Editing and Imputation for Quantitative Survey Data
- Inference and missing data
- Methods and Applications of Linear Models
- A Fast Procedure for Outlier Diagnostics in Large Regression Problems
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