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Author (up) Fierro, R.; Leiva, V.; Balakrishnan, N. pdf  doi
  Title Statistical Inference on a Stochastic Epidemic Model Type
  Year 2015 Publication Communications In Statistics-Simulation And Computation Abbreviated Journal Commun. Stat.-Simul. Comput.  
  Volume 44 Issue 9 Pages 2297-2314  
  Keywords Asymptotic normality; Chi-squared test; Markov chains; Martingale estimators; Maximum likelihood estimators; SIR epidemic model  
  Abstract In this work, we develop statistical inference for the parameters of a discrete-time stochastic SIR epidemic model. We use a Markov chain for describing the dynamic behavior of the epidemic. Specifically, we propose estimators for the contact and removal rates based on the maximum likelihood and martingale methods, and establish their asymptotic distributions. The obtained results are applied in the statistical analysis of the basic reproduction number, a quantity that is useful in establishing vaccination policies. In order to evaluate the population size for which the results are useful, a numerical study is carried out. Finally, a comparison of the maximum likelihood and martingale estimators is conducted by means of Monte Carlo simulations.  
  Address [Fierro, Raul] Pontificia Univ Catolica Valparaiso, Inst Matemat, Valparaiso, Chile, Email:  
  Corporate Author Thesis  
  Publisher Taylor & Francis Inc Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0361-0918 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000356808000008 Approved  
  Call Number UAI @ eduardo.moreno @ Serial 506  
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