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Finite Mixture Models for an Underlying Beta Distribution with an Application to COVID-19 Data

In: Dependent Data in Social Sciences Research

Author

Listed:
  • Cédric Noel

    (University of Luxembourg, Department of Finance)

  • Jang Schiltz

    (University of Luxembourg, Department of Finance)

Abstract

We introduce an extension of Nagin’s finite mixture model to underlying Beta distributions and present our R package trajeR, which allows to calibrate the model. Then, we test the model and illustrate some of the possibilities of trajeR by means of an example with simulated data. In a second part of the chapter, we use this model to analyze COVID-19-related data during the first part of the pandemic. We identify a classification of the world into five groups of countries with respect to the evolution of the contamination rate and show that the median population age is the main predictor of group membership. We do however not see any sign of efficiency of the sanitary measures taken by the different countries against the propagation of the virus.

Suggested Citation

  • Cédric Noel & Jang Schiltz, 2024. "Finite Mixture Models for an Underlying Beta Distribution with an Application to COVID-19 Data," Springer Books, in: Mark Stemmler & Wolfgang Wiedermann & Francis L. Huang (ed.), Dependent Data in Social Sciences Research, edition 2, chapter 0, pages 127-158, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-56318-8_6
    DOI: 10.1007/978-3-031-56318-8_6
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