Parameter estimation for the stochastic SIS epidemic model

Research output: Contribution to conferenceSpeech


In this work [1] we estimate the parameters in the stochastic SIS (susceptible-infected-susceptible) epidemic model [2] by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and 100(1−α)% confidence intervals as well as 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 − α)% joint confidence regions for the pseudo-MLEs. Computer simulations are used to illustrate our theory.
Original languageEnglish
Publication statusUnpublished - Jun 2015
Event26th Numerical Analysis Conference - University of Strathclyde, Glasgow, United Kingdom
Duration: 23 Jun 201526 Jun 2015


Conference26th Numerical Analysis Conference
Country/TerritoryUnited Kingdom


  • susceptible-infected-susceptible model
  • stochastic SIS
  • parameter estimation

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