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  • Titel
    Count Data Time Series Modelling in Julia—The CountTimeSeries.jl Package and Applications
  • Verfasser
    Stapper, Manuel
  • Erschienen
    25.5.2021
  • Anmerkung
    Supplementary Materials are available online at https://www.mdpi.com/article/10.3390/e23060666/s1, Julia and R code for all four applications.
  • Sprache
    Englisch
  • Bibl. Referenz
    Entropy 23 (2021) 6, 666, 1-22
  • Dokumenttyp
    Aufsatz in einer Zeitschrift
  • Schlagwörter (EN)
    count data / time series analysis / Julia programming language
  • URN
    urn:nbn:de:hbz:6-37039752424 
  • DOI
    10.3390/e23060666 
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Abstract
  • A new software package for the Julia language, CountTimeSeries.jl, is under review, which provides likelihood based methods for integer-valued time series. The package’s functionalities are showcased in a simulation study on finite sample properties of Maximum Likelihood (ML) estimation and three real-life data applications. First, the number of newly infected COVID-19 patients is predicted. Then, previous findings on the need for overdispersion and zero inflation are reviewed in an application on animal submissions in New Zealand. Further, information criteria are used for model selection to investigate patterns in corporate insolvencies in Rhineland-Palatinate. Theoretical background and implementation details are described, and complete code for all applications is provided online. The CountTimeSeries package is available at the general Julia package registry.
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