Detect Change Points in Means of High Dimensional Data
Overview
Objective: Implement new methods for detecting change points in high-dimensional time series data. These new methods can be applied to non-Gaussian data, account for spatial and temporal dependence, and detect a wide variety of change-point configurations, including changes near the boundary and changes in close proximity. Additionally, this package helps address the “small n, large p” problem, which occurs in many research contexts. This problem arises when a dataset contains changes that are visually evident but do not rise to the level of statistical significance due to the small number of observations and large number of parameters. The problem is overcome by treating the dimensions as a whole and scaling the test statistics only by its standard deviation, rather than scaling each dimension individually. Due to the computational complexity of the functions, the package runs best on datasets with a relatively large number of attributes but no more than a few hundred observations.
Install
Health
NOTERd filesr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64, r-oldrel-macos-arm64, r-oldrel-macos-x86_64, r-oldrel-windows-x86_64, r-patched-linux-x86_64, r-release-linux-x86_64, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-x86_64
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| ^NOTECRAN incoming feasibilityr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Maintainer: ‘Natasha Stewart <natashastewart@utexas.edu>’
No Authors@R field in DESCRIPTION.
Please add one, modifying
Authors@R: c(person(given = "Jeffrey",
family = "Okamoto",
role = "aut"),
person(given = "Natasha",
family = "Stewart",
role = c("aut", "cre"),
email = "natashastewart@utexas.edu"),
person(given = c("Dr.", "Jun"),
family = "Li",
role = "aut"))
as necessary.- NOTE13 NOTENow
- NOTE14 NOTE2026-03-10
Documentation
- Help pages
- 4
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 50%
Downloads
Dependencies
Installing HDcpDetect adds no packages beyond those that come with R.
Code & Tests
Datasets
People & History
Maintainer since 0.1.0 (2018)
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 0.1.0Latest2018-09-28 · current release
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-09-28
- Total releases
- 1 / 8 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.10
- Bundled data
- 2.2 MB / 3 files
- Download size
- 2.2 MB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("HDcpDetect")Cite the R Observatory
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From data release v2026-10-19, which the citation names so these numbers can be found later. More on citing and the projects behind them.