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Parameter estimation for the stochastic SIS epidemic model

Author

Listed:
  • Jiafeng Pan
  • Alison Gray
  • David Greenhalgh
  • Xuerong Mao

Abstract

In this paper we estimate the parameters in the stochastic SIS epidemic model by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and $$100 (1-\alpha )\%$$ 100 ( 1 - α ) % confidence intervals as well as $$100 (1-\alpha )\%$$ 100 ( 1 - α ) % joint confidence regions by applying least squares techniques. The pseudo-MLEs have almost the same form as the least squares case. We also obtain the exact as well as the asymptotic $$100 (1-\alpha )\%$$ 100 ( 1 - α ) % joint confidence regions for the pseudo-MLEs. Computer simulations are performed to illustrate our theory. Copyright Springer Science+Business Media Dordrecht 2014

Suggested Citation

  • Jiafeng Pan & Alison Gray & David Greenhalgh & Xuerong Mao, 2014. "Parameter estimation for the stochastic SIS epidemic model," Statistical Inference for Stochastic Processes, Springer, vol. 17(1), pages 75-98, April.
    • Handle: RePEc:spr:sistpr:v:17:y:2014:i:1:p:75-98
    DOI: 10.1007/s11203-014-9091-8
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    Cited by:

    1. Wugan Cai & Jiafeng Pan, 2017. "Stochastic Differential Equation Models for the Price of European CO 2 Emissions Allowances," Sustainability, MDPI, vol. 9(2), pages 1-12, February.

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