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LPWC  

Lag Penalized Weighted Correlation for Time Series Clustering
View on CRAN: Click here


Download and install LPWC package within the R console
Install from CRAN:
install.packages("LPWC")

Install from Github:
library("remotes")
install_github("cran/LPWC")

Install by package version:
library("remotes")
install_version("LPWC", "1.0.0")



Attach the package and use:
library("LPWC")
Maintained by
Thevaa Chandereng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-04-12
Latest Update:
Description:
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) .
How to cite:
Thevaa Chandereng (2018). LPWC: Lag Penalized Weighted Correlation for Time Series Clustering. R package version 1.0.0, https://cran.r-project.org/web/packages/LPWC. Accessed 06 Mar. 2026.
Previous versions and publish date:
0.99.2 (2018-04-12 12:52), 0.99.3 (2018-06-04 19:43), 0.99.4 (2018-10-30 17:10), 0.99.5 (2019-03-12 11:06), 1.0.0 (2020-01-23 23:50)
Other packages that cited LPWC R package
View LPWC citation profile
Other R packages that LPWC depends, imports, suggests or enhances
Complete documentation for LPWC
Functions, R codes and Examples using the LPWC R package
Some associated functions: best.lag . comp.corr . corr.bestlag . findC . prep.data . score . simdata . weight.lag . weight . wt.corr . 
Some associated R codes: bestlag.R . comp_corr.R . corr_bestlag.R . findC.R . prep_data.R . score.R . simdata.R . weight.R . weight_lag.R . wt_corr.R .  Full LPWC package functions and examples
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