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Structural identifiability analysis of some highly structured families of statespace models using differential algebra

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Abstract.

In this paper we identify biologically relevant families of models whose structural identifiability analysis could not be performed with available techniques directly. The models considered come from both the immunological and epidemiological literature.

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Acknowledgments.

The authors would like to thank Doctors Barbara Bittner and Gabriella Gomes for providing them with their models and for fruitful discussions. The second author would like to thank Professor Giovanni Pistone, Politecnico di Torino, who hosted her during the research for the present paper (a project funded by MURST ‘‘Ricerca di Base’’, 2001). Two unknown referees are acknowledged for most valuable comments. The authors would like to thank Prof. Saul Jacka for his help in editing the final version of this paper. To the authors alone, however, belongs the responsability for the text.

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Authors and Affiliations

  1. Ufficio Programmazione, Sviluppo e Rilevazioni Statistiche, University of Insubria, Italy

    Gabriella Margaria

  2. Department of Statistics, University of Warwick, UK

    Eva Riccomagno

  3. Department of Biological Sciences, University of Warwick, UK

    Lisa J. White

Authors
  1. Gabriella Margaria
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  2. Eva Riccomagno
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  3. Lisa J. White
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Margaria, G., Riccomagno, E. & White, L. Structural identifiability analysis of some highly structured families of statespace models using differential algebra. J. Math. Biol. 49, 433–454 (2004). https://doi.org/10.1007/s00285-003-0261-3

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  • DOI: https://doi.org/10.1007/s00285-003-0261-3

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