The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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.
| Version: | 0.1.0 |
| Depends: | R (≥ 2.10) |
| Published: | 2018-09-28 |
| Author: | Jeffrey Okamoto [aut], Natasha Stewart [aut], Dr. Jun Li [aut] |
| Maintainer: | Natasha Stewart <natashastewart at utexas.edu> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | HDcpDetect results |
| Reference manual: | HDcpDetect.pdf |
| Package source: | HDcpDetect_0.1.0.tar.gz |
| Windows binaries: | r-devel: HDcpDetect_0.1.0.zip, r-release: HDcpDetect_0.1.0.zip, r-oldrel: HDcpDetect_0.1.0.zip |
| macOS binaries: | r-release (arm64): HDcpDetect_0.1.0.tgz, r-oldrel (arm64): HDcpDetect_0.1.0.tgz, r-release (x86_64): HDcpDetect_0.1.0.tgz, r-oldrel (x86_64): HDcpDetect_0.1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=HDcpDetect to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.