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 |
Author: |
Iván Velasco
[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 |
Documentation:
Downloads:
Linking:
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https://CRAN.R-project.org/package=TSEAL
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