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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "TSrepr" in publications use:'
type: software
license: GPL-3.0-only
title: 'TSrepr: Time Series Representations'
version: 1.1.0
doi: 10.21105/joss.00577
identifiers:
- type: doi
  value: 10.32614/CRAN.package.TSrepr
- type: url
  value: https://github.com/PetoLau/TSrepr/
abstract: Methods for representations (i.e. dimensionality reduction, preprocessing,
  feature extraction) of time series to help more accurate and effective time series
  data mining. Non-data adaptive, data adaptive, model-based and data dictated (clipped)
  representation methods are implemented. Also various normalisation methods (min-max,
  z-score, Box-Cox, Yeo-Johnson), and forecasting accuracy measures are implemented.
authors:
- family-names: Laurinec
  given-names: Peter
  email: tsreprpackage@gmail.com
  orcid: https://orcid.org/0000-0002-3501-8783
preferred-citation:
  type: article
  title: 'TSrepr R package: Time Series Representations'
  authors:
  - family-names: Laurinec
    given-names: Peter
    email: tsreprpackage@gmail.com
    orcid: https://orcid.org/0000-0002-3501-8783
  year: '2018'
  journal: Journal of Open Source Software
  url: https://doi.org/10.21105/joss.00577
  doi: 10.21105/joss.00577
repository: https://cranhaven.r-universe.dev
repository-code: https://github.com/PetoLau/TSrepr
commit: 40b8e1ec78caf32c24f004316b3ea8c83fbc7070
url: https://petolau.github.io/package/
date-released: '2020-07-12'
contact:
- family-names: Laurinec
  given-names: Peter
  email: tsreprpackage@gmail.com
  orcid: https://orcid.org/0000-0002-3501-8783