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dtwclust (version 3.1.1)

Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Description

Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions.

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Install

install.packages('dtwclust')

Monthly Downloads

3,683

Version

3.1.1

License

GPL-3

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Repository

https://github.com/asardaes/dtwclust

Maintainer

Alexis Sarda

Last Published

February 12th, 2017

Functions in dtwclust (3.1.1)

compute_envelop

Time series warping envelops

create_dtwclust

Create formal dtwclust objects

DTW Barycenter Averaging

Cluster validity indices

Basic DTW distance

DTW distance with L2 norm

dtwclust-methods

Methods for dtwclust

Cluster Similarity Matrix

DTW distance matrix guided by Lemire's improved lower bound

Compare partitions

Keogh's DTW lower bound

Shape-based distance

dtwclust-package

Time series clustering along with optimizations for the Dynamic Time Warping distance

Wrapper for simple linear reinterpolation

shape_extraction

Shape average of several time series

Cross-correlation with coefficient normalization

Fast global alignment kernels

Time series clustering

Lemire's improved DTW lower bound

Subset of character trajectories data set

tsclusters-methods

Methods for TSClusters

tsclust-controls

Control parameters for clusterings with tsclust

Wrapper for z-normalization

Time series clustering