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A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

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  • Ortega, Neli R.S.
  • Massad, Eduardo
  • Struchiner, Cláudio José

Abstract

Fuzzy Bayesian tests were performed to evaluate whether the mother’s seroprevalence and children’s seroconversion to measles vaccine could be considered as “high” or “low”. The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi–Sugeno–Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker.

Suggested Citation

  • Ortega, Neli R.S. & Massad, Eduardo & Struchiner, Cláudio José, 2008. "A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(1), pages 1-13.
    • Handle: RePEc:eee:matcom:v:79:y:2008:i:1:p:1-13
    DOI: 10.1016/j.matcom.2007.08.019
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    References listed on IDEAS

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    1. Gil, M. A. & Corral, N. & Gil, P., 1985. "The fuzzy decision problem: An approach to the point estimation problem with fuzzy information," European Journal of Operational Research, Elsevier, vol. 22(1), pages 26-34, October.
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