Package: mlmts
Type: Package
Title: Machine Learning Algorithms for Multivariate Time Series
Version: 1.0.0
Authors@R: c(
    person("Angel", "Lopez-Oriona", email = "oriona38@hotmail.com", 
    role = c("aut", "cre")),
    person("Jose", "A. Vilar", role = "aut"))
Description: An implementation of several machine learning algorithms for 
    multivariate time series. The package includes functions allowing the
    execution of clustering, classification or outlier detection methods,
    among others. It also incorporates a collection of multivariate time
    series datasets which can be used to analyse the performance of new
    proposed algorithms. Practitioners from a broad variety of fields could
    benefit from the general framework provided by 'mlmts'.
License: GPL-2
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Depends: R (>= 4.0.0)
RoxygenNote: 7.1.2
Imports: quantspec, waveslim, Rfast, TSclust, forecast, tseries, TSA,
        tsfeatures, tseriesChaos, freqdom, e1071, dtw, base, psych,
        complexplus, MTS, Matrix, ggplot2, multiwave, MASS, fda.usc,
        TSdist, evolqg, geigen, DescTools, pracma, pspline, Rdpack,
        stats, ClusterR, AID, caret, ranger
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2022-02-18 23:36:13 UTC; angel
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Author: Angel Lopez-Oriona [aut, cre],
  Jose A. Vilar [aut]
Maintainer: Angel Lopez-Oriona <oriona38@hotmail.com>
Repository: CRAN
Date/Publication: 2022-02-21 08:50:05 UTC
Built: R 4.0.5; ; 2022-02-22 12:30:56 UTC; unix
