Large-Scale Datastreams Surveillance via Pattern-Oriented-Sampling
DOI10.1080/01621459.2020.1819295OpenAlexW3084208473MaRDI QIDQ5885104
Changliang Zou, Nan Chen, Haojie Ren, Run-Ze Li
Publication date: 27 March 2023
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/01621459.2020.1819295
kernel smoothingoptimal samplingsequential change detectiongeneralized likelihood ratio methodstatistical monitoringdesign-adaptive test
Hypothesis testing in multivariate analysis (62H15) Applications of statistics in engineering and industry; control charts (62P30) Sequential statistical analysis (62L10)
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Cites Work
- A consistent test of functional form via nonparametric estimation techniques
- Efficient scalable schemes for monitoring a large number of data streams
- Sequential multi-sensor change-point detection
- Distribution-free cumulative sum control charts using bootstrap-based control limits
- Using the generalized likelihood ratio statistic for sequential detection of a change-point
- High-dimensional change-point detection under sparse alternatives
- Data-driven rate-optimal specification testing in regression models
- Multivariate Statistical Process Control Using LASSO
- Decentralized quickest change detection
- A novel approach to detection of intrusions in computer networks via adaptive sequential and batch-sequential change-point detection methods
- High Dimensional Change Point Estimation via Sparse Projection
- Adaptive Rejection Sampling for Gibbs Sampling
- Fast Subset Scan for Spatial Pattern Detection
- A Reference-Free Cuscore Chart for Dynamic Mean Change Detection and a Unified Framework for Charting Performance Comparison
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