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.

LPWC: Lag Penalized Weighted Correlation for Time Series Clustering

Computes a time series distance measure for clustering based on weighted correlation and introduction of lags. The lags capture delayed responses in a time series dataset. The timepoints must be specified. T. Chandereng, A. Gitter (2020) <doi:10.1186/s12859-019-3324-1>.

Version: 1.0.0
Depends: R (≥ 3.0.2)
Imports: nleqslv
Suggests: testthat, rmarkdown, pkgdown, ggplot2, knitr, devtools
Published: 2020-01-23
Author: Thevaa Chandereng ORCID iD [aut, cre, cph], Anthony Gitter ORCID iD [aut, cph]
Maintainer: Thevaa Chandereng <chandereng at wisc.edu>
BugReports: https://github.com/gitter-lab/LPWC/issues
License: MIT + file LICENSE
URL: https://github.com/gitter-lab/LPWC
NeedsCompilation: yes
Citation: LPWC citation info
Materials: README NEWS
CRAN checks: LPWC results

Documentation:

Reference manual: LPWC.pdf
Vignettes: Cluster time series data

Downloads:

Package source: LPWC_1.0.0.tar.gz
Windows binaries: r-devel: LPWC_1.0.0.zip, r-release: LPWC_1.0.0.zip, r-oldrel: LPWC_1.0.0.zip
macOS binaries: r-release (arm64): LPWC_1.0.0.tgz, r-oldrel (arm64): LPWC_1.0.0.tgz, r-release (x86_64): LPWC_1.0.0.tgz, r-oldrel (x86_64): LPWC_1.0.0.tgz
Old sources: LPWC archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=LPWC 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.