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On a Non-homogeneous Gompertz-Type Diffusion Process: Inference and First Passage Time

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Computer Aided Systems Theory – EUROCAST 2017 (EUROCAST 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10672))

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Abstract

A stochastic diffusion model based on a generalized Gompertz deterministic growth in which the carrying capacity depends on the initial size of the population is considered. The growth parameter of the process is then modified by introducing a time-dependent exogenous term. The first passage time problem is considered and a two-step procedure to estimate the model is proposed. Simulation study is also provided for suitable choices of the exogenous term.

This work was supported in part by the Ministerio de Economia y Competitividad, Spain, under Grant MTM2014-58061-P and partially by INDAM-GNCS.

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Author information

Authors and Affiliations

  1. Dip. di Scienze Economiche e Statistiche, Università di Salerno, Fisciano, Italy

    Giuseppina Albano

  2. Dip. di Informatica, Università di Salerno, Fisciano, Italy

    Virginia Giorno

  3. Dpto. de Estadística e Investigación Operativa, Universidad de Granada, Granada, Spain

    Patricia Román-Román & Francisco Torres-Ruiz

Authors
  1. Giuseppina Albano
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  2. Virginia Giorno
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  3. Patricia Román-Román
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  4. Francisco Torres-Ruiz
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Corresponding author

Correspondence to Giuseppina Albano .

Editor information

Editors and Affiliations

  1. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Roberto Moreno-Díaz

  2. Johannes Kepler University Linz, Linz, Austria

    Franz Pichler

  3. University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Alexis Quesada-Arencibia

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Albano, G., Giorno, V., Román-Román, P., Torres-Ruiz, F. (2018). On a Non-homogeneous Gompertz-Type Diffusion Process: Inference and First Passage Time. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory – EUROCAST 2017. EUROCAST 2017. Lecture Notes in Computer Science(), vol 10672. Springer, Cham. https://doi.org/10.1007/978-3-319-74727-9_6

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  • DOI: https://doi.org/10.1007/978-3-319-74727-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-74726-2

  • Online ISBN: 978-3-319-74727-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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