Estimation of parameters for the SDE SIS epidemic model

Research output: Contribution to conferencePresentation/Speech

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 $100(1-\alpha)\%$ confidence intervals as well as $100(1-\alpha)\%$ 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 $100(1-\alpha)\%$ joint confidence regions for the pseudo-MLEs. Computer simulations are performed to illustrate our theory.
Original languageEnglish
Publication statusUnpublished - 2012
EventWorkshop on Stochastic Modelling in Ecosystems - Glasgow, United Kingdom
Duration: 11 Jun 201212 Jun 2012

Conference

ConferenceWorkshop on Stochastic Modelling in Ecosystems
Country/TerritoryUnited Kingdom
CityGlasgow
Period11/06/1212/06/12

Keywords

  • Stochastic SIS epidemic model
  • pseudo-maximum likelihood estimation
  • least squares estimation
  • confidence interval
  • confidence region
  • asymptotic estimator

Fingerprint

Dive into the research topics of 'Estimation of parameters for the SDE SIS epidemic model'. Together they form a unique fingerprint.

Cite this