Package: onlineCOV
Type: Package
Title: Online Change Point Detection in High-Dimensional Covariance
        Structure
Version: 1.3
Date: 2020-03-14
Author: Lingjun Li and Jun Li
Maintainer: Jun Li <jli49@kent.edu>
Description: Implement a new stopping rule to detect anomaly in the covariance structure of high-dimensional online data. The detection procedure can be applied to Gaussian or non-Gaussian data with a large number of components. Moreover, it allows both spatial and temporal dependence in data. The dependence can be estimated by a data-driven procedure. The level of threshold in the stopping rule can be determined at a pre-selected average run length. More detail can be seen in Li, L. and Li, J. (2020) "Online Change-Point Detection in High-Dimensional Covariance Structure with Application to Dynamic Networks." <arXiv:1911.07762>.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2020-03-20 17:34:23 UTC; Hico
Repository: CRAN
Date/Publication: 2020-03-23 09:40:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 20:55:12 UTC; unix
Archs: onlineCOV.so.dSYM
