CRAN/E | gStream

gStream

Graph-Based Sequential Change-Point Detection for Streaming Data

Installation

About

Uses an approach based on k-nearest neighbor information to sequentially detect change-points. Offers analytic approximations for false discovery control given user-specified average run length. Can be applied to any type of data (high-dimensional, non-Euclidean, etc.) as long as a reasonable similarity measure is available. See references (1) Chen, H. (2019) Sequential change-point detection based on nearest neighbors. The Annals of Statistics, 47(3):1381-1407. (2) Chu, L. and Chen, H. (2018) Sequential change-point detection for high-dimensional and non-Euclidean data .

Key Metrics

Version 0.2.0
R ≥ 3.0.1
Published 2019-05-01 1815 days ago
Needs compilation? no
License GPL-2
License GPL-3
CRAN checks gStream results

Downloads

Yesterday 11 0%
Last 7 days 25 +32%
Last 30 days 135 -8%
Last 90 days 626 +53%
Last 365 days 1.861 -30%

Maintainer

Maintainer

Hao Chen

hxchen@ucdavis.edu

Authors

Hao Chen
Lynna Chu

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

gStream archive

Depends

R ≥ 3.0.1