Package: tsfeatures
Title: Time Series Feature Extraction
Version: 1.1
Authors@R: c(
    person("Rob", "Hyndman", email = "Rob.Hyndman@monash.edu", role = c("aut","cre"), comment = c(ORCID = "0000-0002-2140-5352")),
    person("Yanfei", "Kang", role = "aut", comment = c(ORCID = "0000-0001-8769-6650")),
    person("Pablo", "Montero-Manso", email="p.montero.manso@udc.es", role="aut"),
    person("Thiyanga", "Talagala", role = "aut", comment=c(ORCID = "0000-0002-0656-9789")),
    person("Earo", "Wang", role = "aut", comment=c(ORCID = "0000-0001-6448-5260")),
    person("Yangzhuoran", "Yang", email = "Fin.Yang@monash.edu", role = "aut"),
    person("Mitchell", "O'Hara-Wild", role="aut", comment=c(ORCID = "0000-0001-6729-7695")),
    person("Souhaib", "Ben Taieb", role = "ctb"),
    person("Cao", "Hanqing", role="ctb"),
    person("D K", "Lake", email="dlake@virginia.edu", role="ctb"),
    person("Nikolay", "Laptev", role="ctb"),
    person("J R", "Moorman", role="ctb"))
Description: 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.
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
License: GPL-3
ByteCompile: true
URL: https://pkg.robjhyndman.com/tsfeatures/
BugReports: https://github.com/robjhyndman/tsfeatures/issues/
RoxygenNote: 7.2.1
Roxygen: list(markdown = TRUE, roclets=c('rd', 'collate', 'namespace'))
VignetteBuilder: knitr
Encoding: UTF-8
