Time Series Clustering with Dynamic Time Warping
stats, methods, caTools, ggplot2, reshape2, modeltools
Time series clustering using different techniques related to the Dynamic Time Warping distance
and its corresponding lower bounds. Additionally, an implementation of k-Shape clustering is available.

stats, methods, caTools, reshape2, modeltools

Time series clustering using different techniques related to the
Dynamic Time Warping distance and its corresponding lower bounds. Additionally,
an implementation of k-Shape clustering is available.

stats, methods, caTools, reshape2, modeltools, doRNG, parallel

Time Series Clustering with Dynamic Time Warping Distance
stats, methods, caTools, reshape2, foreach, parallel
Time series clustering using different techniques related to the
Dynamic Time Warping distance and its corresponding lower bounds. Additionally,
an implementation of k-Shape clustering is available, and the package can be
easily extended with custom distance measures and centroid definitions.
'DBA.R' 'NCCc.R' 'SBD.R' 'TADPole.R' 'all_cent.R' 'dtw-lb.R'
'dtw2.R' 'dtwclust-classes.R' 'dtwclust-methods.R' 'dtwclust.R'
'dtwdistfun.R' 'kcca-list.R' 'lb-improved.R' 'lb-keogh.R'
'utils.R' 'pkg.R' 'reinterpolate.R' 'shape-extraction.R'
'uciCT.R' 'zscore.R'

Time Series Clustering with Optimizations for the Dynamic Time
Warping Distance
stats, utils, methods, flexclust, caTools, reshape2, foreach,
parallel
Time series clustering with optimized techniques related to the
Dynamic Time Warping distance and its corresponding lower bounds.
Implementations of k-Shape, TADPole and fuzzy clustering are available.
The functionality can be easily extended with custom distance measures
and centroid definitions.
'DBA.R' 'NCCc.R' 'SBD.R' 'TADPole.R' 'all_cent.R' 'ddist.R'
'dtw-lb.R' 'dtw2.R' 'dtwclust-classes.R' 'dtwclust-methods.R'
'dtwclust.R' 'kcca-list.R' 'lb-improved.R' 'lb-keogh.R'
'utils.R' 'pkg.R' 'reinterpolate.R' 'shape-extraction.R'
'uciCT.R' 'zscore.R'

Time Series Clustering Along with Optimizations for the Dynamic
Time Warping Distance
R (>= 3.2.0), proxy, dtw, ggplot2, rngtools
Time series clustering along with optimized techniques related
to the Dynamic Time Warping distance and its corresponding lower bounds.
Implementations of k-Shape, TADPole and fuzzy clustering are available.
The functionality can be easily extended with custom distance measures
and centroid definitions.