TSEAL: Time Series Analysis Library

The library allows to perform a multivariate time series classification based on the use of Discrete Wavelet Transform for feature extraction, a step wise discriminant to select the most relevant features and finally, the use of a linear or quadratic discriminant for classification. Note that all these steps can be done separately which allows to implement new steps. Velasco, I., Sipols, A., de Blas, C. S., Pastor, L., & Bayona, S. (2023) <doi:10.1186/S12938-023-01079-X>. Percival, D. B., & Walden, A. T. (2000,ISBN:0521640687). Maharaj, E. A., & Alonso, A. M. (2014) <doi:10.1016/j.csda.2013.09.006>.

Version: 0.1.2
Depends: R (≥ 4.3.0)
Imports: bigmemory, caret, checkmate, magrittr, MASS, methods, parallel, parallelly, pryr, statcomp, stats, synchronicity, utils, waveslim, wdm
Suggests: spelling, testthat (≥ 3.0.0)
Published: 2024-05-01
DOI: 10.32614/CRAN.package.TSEAL
Author: Iván Velasco ORCID iD [aut, cre, cph]
Maintainer: Iván Velasco <ivan.velasco at urjc.es>
BugReports: https://github.com/vg-lab/TSEAL/issues
License: Artistic-2.0
URL: https://github.com/vg-lab/TSEAL
NeedsCompilation: no
Language: en-US
In views: TimeSeries
CRAN checks: TSEAL results


Reference manual: TSEAL.pdf


Package source: TSEAL_0.1.2.tar.gz
Windows binaries: r-devel: TSEAL_0.1.2.zip, r-release: TSEAL_0.1.2.zip, r-oldrel: TSEAL_0.1.2.zip
macOS binaries: r-release (arm64): TSEAL_0.1.2.tgz, r-oldrel (arm64): TSEAL_0.1.2.tgz, r-release (x86_64): TSEAL_0.1.2.tgz, r-oldrel (x86_64): TSEAL_0.1.2.tgz


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