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 (2018) <doi:10.1101/292615>.

Version: 0.99.5
Depends: R (≥ 3.0.2)
Suggests: testthat, rmarkdown, pkgdown, ggplot2, knitr, devtools
Published: 2019-03-12
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: no
Citation: LPWC citation info
Materials: README
CRAN checks: LPWC results


Reference manual: LPWC.pdf
Vignettes: Cluster time series data
Package source: LPWC_0.99.5.tar.gz
Windows binaries: r-devel: LPWC_0.99.5.zip, r-release: LPWC_0.99.5.zip, r-oldrel: LPWC_0.99.5.zip
OS X binaries: r-release: LPWC_0.99.5.tgz, r-oldrel: LPWC_0.99.5.tgz
Old sources: LPWC archive


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