Computation of projection regression depth and its induced median
From MaRDI portal
Publication:830082
DOI10.1016/j.csda.2021.107184OpenAlexW3123887329MaRDI QIDQ830082
Publication date: 7 May 2021
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1905.11846
Related Items (2)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Computing multiple-output regression quantile regions
- Bias-robust estimates of regression based on projections
- Multivariate dispersion, central regions and depth. The lift zonoid approach
- Exact computation of bivariate projection depth and the Stahel-Donoho estimator
- On a notion of data depth based on random simplices
- Trimmed and Winsorized means based on a scaled deviation
- Computing zonoid trimmed regions of dimension \(d>2\)
- The random Tukey depth
- Breakdown properties of location estimates based on halfspace depth and projected outlyingness
- Primal-dual methods for vertex and facet enumeration
- An interior-point algorithm for nonconvex nonlinear programming
- Zonoid trimming for multivariate distributions
- Projection-based depth functions and associated medians
- Robustness of deepest regression
- The deepest regression method
- General notions of statistical depth function.
- Continuity of halfspace depth contours and maximum depth estimators: Diagnostics of depth-related methods
- Absolute approximation of Tukey depth: theory and experiments
- On general notions of depth for regression
- Large sample properties of the regression depth induced median
- Data depths satisfying the projection property
- Least Median of Squares Regression
- Trimmed and winsorized standard deviations based on a scaled deviation
- The multivariate L 1 -median and associated data depth
- LOQO:an interior point code for quadratic programming
- Regression Depth
- The Least Trimmed Differences Regression Estimator and Alternatives
- A new approach for the computation of halfspace depth in high dimensions
- Computing Halfspace Depth and Regression Depth
- Robustness and Complex Data Structures
- Partitions ofN-Space by Hyperplanes
- Robust Statistics
This page was built for publication: Computation of projection regression depth and its induced median