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

Tim Kaiser
Additional contact information
Tim Kaiser: University of Greifswald

No azc74, OSF Preprints from Center for Open Science

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.

Date: 2017-11-13
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/5a098f939ad5a1026b03dd7c/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:azc74

DOI: 10.31219/osf.io/azc74

Access Statistics for this paper

More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().