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Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)

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  • Jachner, Stefanie
  • Gerald van den Boogaart, K.
  • Petzoldt, Thomas

Abstract

Results of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic differences between measurement and simulation. However, for the application of such models it is often more important to reproduce essential patterns instead of seemingly exact numerical values. This paper presents techniques to identify patterns and numerical methods to measure the consistency of patterns between observations and model results. An orthogonal set of deviance measures for absolute, relative and ordinal scale was compiled to provide informations about the type of difference. Furthermore, two different approaches accounting for time shifts were presented. The first one transforms the time to take time delays and speed differences into account. The second one describes known qualitative criteria dividing time series into interval units in accordance to their main features. The methods differ in their basic concepts and in the form of the resulting criteria. Both approaches and the deviance measures discussed are implemented in an R package. All methods are demonstrated by means of water quality measurements and simulation data. The proposed quality criteria allow to recognize systematic differences and time shifts between time series and to conclude about the quantitative and qualitative similarity of patterns.

Suggested Citation

  • Jachner, Stefanie & Gerald van den Boogaart, K. & Petzoldt, Thomas, 2007. "Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i08).
  • Handle: RePEc:jss:jstsof:v:022:i08
    DOI: http://hdl.handle.net/10.18637/jss.v022.i08
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    Cited by:

    1. repec:jss:jstsof:22:i09 is not listed on IDEAS
    2. Portell, Xavier & Gras, Anna & Ginovart, Marta, 2014. "INDISIM-Saccha, an individual-based model to tackle Saccharomyces cerevisiae fermentations," Ecological Modelling, Elsevier, vol. 279(C), pages 12-23.
    3. Petzoldt, Thomas & Rinke, Karsten, 2007. "simecol: An Object-Oriented Framework for Ecological Modeling in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i09).
    4. Erden, Lutfi & Ozkan, Ibrahim, 2014. "Determinants of international transmission of business cycles to Turkish economy," Economic Modelling, Elsevier, vol. 36(C), pages 383-390.
    5. Piotr Boniecki & Małgorzata Idzior-Haufa & Agnieszka A. Pilarska & Krzysztof Pilarski & Alicja Kolasa-Wiecek, 2019. "Neural Classification of Compost Maturity by Means of the Self-Organising Feature Map Artificial Neural Network and Learning Vector Quantization Algorithm," IJERPH, MDPI, vol. 16(18), pages 1-9, September.
    6. Lisa De Mattéo & Yan Holtz & Vincent Ranwez & Sèverine Bérard, 2018. "Efficient algorithms for Longest Common Subsequence of two bucket orders to speed up pairwise genetic map comparison," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-19, December.
    7. repec:jss:jstsof:22:i01 is not listed on IDEAS
    8. Kneib, Thomas & Petzoldt, Thomas, 2007. "Introduction to the Special Volume on "Ecology and Ecological Modeling in R"," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 22(i01).
    9. Barbosa, Carolina Cerqueira & Calijuri, Maria do Carmo & Anjinho, Phelipe da Silva & dos Santos, André Cordeiro Alves, 2023. "An integrated modeling approach to predict trophic state changes in a large Brazilian reservoir," Ecological Modelling, Elsevier, vol. 476(C).
    10. Piou, Cyril & Berger, Uta & Grimm, Volker, 2009. "Proposing an information criterion for individual-based models developed in a pattern-oriented modelling framework," Ecological Modelling, Elsevier, vol. 220(17), pages 1957-1967.

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