Outlier detection for multivariate skew-normal data: a comparative study

DOI10.1080/00949655.2011.636364zbMath1431.62218OpenAlexW1981104564MaRDI QIDQ2862374

No author found.

Publication date: 15 November 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2011.636364

zbMATH Keywords

skew-normal distributionoutlier detectiondata depthoutlyingness

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items

Evaluation of outlier detection method performance in symmetric multivariate distributions, Outlier-free merging of homogeneous groups of pre-classified observations under contamination, Power of depth-based nonparametric tests for multivariate locations, On the robustness to symmetry of some nonparametric multivariate one-sample sign-type tests, Truncated normal distribution-based EWMA control chart for monitoring the process mean in the presence of outliers, Boxplot-Based Outlier Detection for the Location-Scale Family

Cites Work

• Error rates for multivariate outlier detection
• Outlier identification in high dimensions
• An adjusted boxplot for skewed distributions
• Nonparametric depth-based multivariate outlier identifiers, and masking robustness properties
• \(M\)-estimation, convexity and quantiles
• General notions of statistical depth function.
• The multivariate skew-normal distribution
• Multivariate Outlier Detection With High-Breakdown Estimators
• Boxplot-Based Outlier Detection for the Location-Scale Family
• The elements of statistical learning. Data mining, inference, and prediction
• Unnamed Item