Anomaly Detection in High-Dimensional Data

DOI10.1080/10618600.2020.1807997OpenAlexW3048727804MaRDI QIDQ5066401

Rob Hyndman, Priyanga Dilini Talagala, Kate A. Smith-Miles

Publication date: 29 March 2022

Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1908.04000

zbMATH Keywords

extreme value theoryhigh-dimensional datatemporal datanearest neighbor searchingunsupervised outlier detection

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (4)

2-D Rayleigh autoregressive moving average model for SAR image modeling ⋮ Subset Multivariate Collective and Point Anomaly Detection ⋮ Leave-One-Out Kernel Density Estimates for Outlier Detection ⋮ stray

Uses Software

• R
• ggplot2
• FNN
• HDoutliers
• LOF

Cites Work

• Unnamed Item
• Multivariate Outliers and the O3 Plot
• Anomaly Detection in Streaming Nonstationary Temporal Data
• Towards objective measures of algorithm performance across instance space
• A survey of outlier detection methodologies
• ggplot2
• Outlier Analysis
• Additive Outlier Detection Via Extreme-Value Theory
• Printer graphics for clustering
• Estimation of Parameters and Larger Quantiles Based on the k Largest Observations
• Detection of outliers in simple circular regression models using the mean circular error statistic
• Data Mining and Knowledge Discovery Handbook

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