IDEAS home Printed from https://ideas.repec.org/p/osf/osfxxx/azc74.html
   My bibliography  Save this paper

dyncomp: an R package for Estimating the Complexity of Short Time Series

Author

Listed:
  • Kaiser, Tim

    (University of Greifswald)

Abstract

As non-linear time series analysis becomes more and more wide-spread, measures that can be applied to short time series with relatively low temporal resolution are in demand. The author introduces a complexity parameter for time series based on fluctuation and distribution of values, as well as its R implementation. This parameter is validated with a known chaotic dynamic system. It is shown that the parameter’s validity approaches or even surpasses that of most similar measures. In another step of validation, data from time series of daily ratings of anxiety and depression symptoms is used to show the utility of the proposed measure.

Suggested Citation

  • Kaiser, Tim, 2017. "dyncomp: an R package for Estimating the Complexity of Short Time Series," OSF Preprints azc74, Center for Open Science.
  • Handle: RePEc:osf:osfxxx:azc74
    DOI: 10.31219/osf.io/azc74
    as

    Download full text from publisher

    File URL: https://osf.io/download/5a098f939ad5a1026b03dd7c/
    Download Restriction: no

    File URL: https://libkey.io/10.31219/osf.io/azc74?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:osf:osfxxx:azc74. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: OSF (email available below). General contact details of provider: https://osf.io/preprints/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.