doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.">

tsfeatures: Time Series Feature Extraction (original) (raw)

Methods for extracting various features from time series data. The features provided are those from Hyndman, Wang and Laptev (2013) <doi:10.1109/ICDMW.2015.104>, Kang, Hyndman and Smith-Miles (2017) <doi:10.1016/j.ijforecast.2016.09.004> and from Fulcher, Little and Jones (2013) <doi:10.1098/rsif.2013.0048>. Features include spectral entropy, autocorrelations, measures of the strength of seasonality and trend, and so on. Users can also define their own feature functions.

Version: 1.1.1
Depends: R (≥ 3.6.0)
Imports: fracdiff, forecast (≥ 8.3), purrr, RcppRoll (≥ 0.2.2), stats, tibble, tseries, urca, future, furrr
Suggests: testthat, knitr, rmarkdown, ggplot2, tidyr, dplyr, Mcomp, GGally
Published: 2023-08-28
DOI: 10.32614/CRAN.package.tsfeatures
Author: Rob Hyndman ORCID iD [aut, cre], Yanfei Kang ORCID iD [aut], Pablo Montero-Manso [aut], Mitchell O'Hara-WildORCID iD [aut], Thiyanga Talagala ORCID iD [aut], Earo Wang ORCID iD [aut], Yangzhuoran Yang [aut], Souhaib Ben Taieb [ctb], Cao Hanqing [ctb], D K Lake [ctb], Nikolay Laptev [ctb], J R Moorman [ctb], Bohan Zhang [ctb]
Maintainer: Rob Hyndman <Rob.Hyndman at monash.edu>
BugReports: https://github.com/robjhyndman/tsfeatures/issues
License: GPL-3
URL: https://pkg.robjhyndman.com/tsfeatures/,https://github.com/robjhyndman/tsfeatures
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: tsfeatures results

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