Package: LPWC 1.0.0

Thevaa Chandereng

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>.

Authors:Thevaa Chandereng [aut, cre, cph], Anthony Gitter [aut, cph]

LPWC_1.0.0.tar.gz
LPWC_1.0.0.zip(r-4.7)LPWC_1.0.0.zip(r-4.6)LPWC_1.0.0.zip(r-4.5)
LPWC_1.0.0.tgz(r-4.6-any)LPWC_1.0.0.tgz(r-4.5-any)
LPWC_1.0.0.tar.gz(r-4.7-any)LPWC_1.0.0.tar.gz(r-4.6-any)
LPWC_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
LPWC/json (API)

# Install 'LPWC' in R:

install.packages('LPWC', repos = c('https://gitter-lab.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/gitter-lab/lpwc/issues

Datasets:

simdata - Example datasets for LPC

On CRAN:

bioinformatics clustering time-series

5.28 score 21 stars 18 scripts 39 downloads 1 mentions 9 exports 1 dependencies

Last updated from:56d076d31a. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	143
source / vignettes	OK	189
linux-release-x86_64	OK	145
macos-release-arm64	OK	125
macos-oldrel-arm64	OK	132
windows-devel	OK	81
windows-release	OK	104
windows-oldrel	OK	75
wasm-release	OK	156

Exports:best.lag comp.corr corr.bestlag findC prep.data score weight weight.lag wt.corr

Dependencies:nleqslv

LPWC: Lag Penalized Weighted Correlation for Clustering Short Time Series

Rendered fromLPWC.Rmdusingknitr::rmarkdown

Last update: 2020-01-23
Started: 2018-04-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Best Lag	best.lag
Computing corr	comp.corr
Computes best lag correlation	corr.bestlag
Finding best C	findC
Preparing Data	prep.data
Score of Lags	score
Example datasets for LPC	simdata
Weight in correlation	weight
Weight Lag	weight.lag
Weighted correlation	wt.corr