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TSclust (version 1.1)

Time series clustering utilities

Description

This package contains a set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.

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Version

Install

install.packages('TSclust')

Monthly Downloads

7,827

Version

1.1

License

GPL-2

Maintainer

Pablo Montero

Last Published

July 16th, 2013

Functions in TSclust (1.1)

TSclust

Package for Time Series Clustering.
diss.AR.MAH

Model-based Dissimilarity Proposed by Maharaj (1996, 2000)
diss.AR.LPC.CEPS

Dissimilarity Based on LPC Cepstral Coefficients
diss.INT.PER

Integrated Periodogram Based Dissimilarity
synthetic.tseries

Synthetic Time Series for Clustering Performace Comparisons.
diss.SPEC.ISD

Dissimilarity Based on the Integrated Squared Difference between the Log-Spectra
diss.COR

Correlation-based Dissimilarity
diss.PRED

Dissimilarity Measure Based on Nonparametric Forecast
diss.DWT

Dissimilarity for Time Series Based on Wavelet Feature Extraction
diss.AR.PIC

Model-based Dissimilarity Measure Proposed by Piccolo (1990)
electricity

Hourly Electricity Prices in the Spanish Market
diss.SPEC.GLK

Dissimilarity based on the Generalized Likelihood Ratio Test
interest.rates

Long-Term Interest Rates from 1995 to 2012
diss.PER

Periodogram Based Dissimilarity
pvalues.clust

Clustering Algorithm Based on p-values.
diss.SPEC.LLR

General Spectral Dissimilarity Measure Using Local-Linear Estimation of the Log-Spectra
diss.ACF

Autocorrelation-based Dissimilarity
cluster.evaluation

Clustering Evaluation Index Based on Known Ground Truth
diss.CORT

Dissimilarity Index Combining Temporal Correlation and Raw Values Behaviors