CUSUM multi-chart for detecting unknown abrupt changes under finite measure space for network observation sequences
From MaRDI portal
Publication:5163040
DOI10.1080/02331888.2021.1943394zbMath1477.62218OpenAlexW3176916859MaRDI QIDQ5163040
No author found.
Publication date: 8 November 2021
Published in: Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/02331888.2021.1943394
Nonparametric hypothesis testing (62G10) Optimal statistical designs (62K05) Sequential statistical analysis (62L10) Optimal stopping in statistics (62L15) Probabilistic graphical models (62H22)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A CUSUM control chart for monitoring the variance when parameters are estimated
- Logit models and logistic regressions for social networks. I: An introduction to Markov graphs and \(p^*\)
- Bayesian anomaly detection methods for social networks
- Sequential analysis. Tests and confidence intervals
- Optimal stopping times for detecting changes in distributions
- A generalized EWMA control chart and its comparison with the optimal EWMA, CUSUM and GLR schemes.
- Using the generalized likelihood ratio statistic for sequential detection of a change-point
- Discrete temporal models of social networks
- Graph-based change-point detection
- Sequential change-point detection based on nearest neighbors
- Model-based clustering of large networks
- Social Network Monitoring: Aiming to Identify Periods of Unusually Increased Communications Between Parties of Interest
- Bayesian Quickest Change-Point Detection With Sampling Right Constraints
- Markov Graphs
- Ideal spatial adaptation by wavelet shrinkage
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Detection and Diagnosis of Unknown Abrupt Changes Using CUSUM Multi-Chart Schemes
- Procedures for Reacting to a Change in Distribution
- A Separable Model for Dynamic Networks
