Multiple outlier detection in multivariate data using self-organizing maps
From MaRDI portal
Publication:2488397
DOI10.1007/BF02789702zbMath1092.62098MaRDI QIDQ2488397
Ashok K. Nag, Amit Mitra, Sharmishtha Mitra
Publication date: 24 May 2006
Published in: Computational Statistics (Search for Journal in Brave)
Factor analysis and principal components; correspondence analysis (62H25) Neural nets and related approaches to inference from stochastic processes (62M45)
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Cites Work
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- On the relation between S-estimators and M-estimators of multivariate location and covariance
- On the stationary state of Kohonen's self-organizing sensory mapping
- Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
- Convergence properties of Kohonen's topology conserving maps: Fluctuations, stability, and dimension selection
- Self-organization and associative memory.
- Robust m-estimators of multivariate location and scatter
- The feasible solution algorithm for the minimum covariance determinant estimator in multivariate data
- Robustness properties of \(S\)-estimators of multivariate location and shape in high dimension
- Some Results on the Existence, Uniqueness, and Computation of the M-Estimates of Multivariate Location and Scatter
- Robust Estimation of Dispersion Matrices and Principal Components
- Robust Procedures in Multivariate Analysis I: Robust Covariance Estimation
- Robust Procedures in Multivariate Analysis II. Robust Canonical Variate Analysis
- Computable Robust Estimation of Multivariate Location and Shape in High Dimension Using Compound Estimators
- Fast Very Robust Methods for the Detection of Multiple Outliers
- Identification of Outliers in Multivariate Data
- Robust Statistics
- Self-organizing maps.