Influence Functions and Efficiencies of k-Step Hettmansperger–Randles Estimators for Multivariate Location and Regression
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Publication:5280268
DOI10.1007/978-3-319-39065-9_11zbMath1366.62141OpenAlexW2521774855WikidataQ110021900 ScholiaQ110021900MaRDI QIDQ5280268
Publication date: 20 July 2017
Published in: Robust Rank-Based and Nonparametric Methods (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-319-39065-9_11
efficiencyinfluence functionaffine equivariancemultivariate regressionspatial signshape matrixlocation vectorHettmansperger-Randles estimators
Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20) Nonparametric robustness (62G35) Linear regression; mixed models (62J05)
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Cites Work
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- Invariant Co-Ordinate Selection
- A canonical definition of shape
- Multivariate nonparametric methods with R. An approach based on spatial signs and ranks.
- \(k\)-step shape estimators based on spatial signs and ranks
- Asymptotic distributions of robust shape matrices and scales
- A distribution-free M-estimator of multivariate scatter
- Asymptotic behaviour of S-estimates of multivariate location parameters and dispersion matrices
- Robust m-estimators of multivariate location and scatter
- Robust principal component analysis for functional data. (With comments)
- Some robust estimates of principal components
- The \(k\)-step spatial sign covariance matrix
- Asymptotic theory of least distances estimate in multivariate linear models
- A practical affine equivariant multivariate median
- Estimates of Regression Coefficients Based on the Sign Covariance Matrix
- Affine Invariant Multivariate Sign and Rank Tests and Corresponding Estimates: a Review
- Robust Nonparametric Statistical Methods
- On the Breakdown Properties of Some Multivariate M-Functionals*
- Sign and rank covariance matrices