Parameter estimation for the stochastic SIS epidemic model

Research output: Contribution to conferenceSpeech

Abstract

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

Conference

Conference26th Numerical Analysis Conference
CountryUnited Kingdom
CityGlasgow
Period23/06/1526/06/15

Keywords

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

Cite this

Gray, A., Pan, J., Greenhalgh, D., & Mao, X. (2015). Parameter estimation for the stochastic SIS epidemic model. 26th Numerical Analysis Conference, Glasgow, United Kingdom.