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Fixed accuracy estimation for chain binomial models

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  • Huggins, R. M.

Abstract

In many epidemic models the initial infection rate, suitably defined, plays a major role in determining the probability of an outbreak of a disease becoming a major epidemic. Here we model the epidemic as a chain binomial model and consider an approximate maximum likelihood estimator of the infection rate. It is shown that under mild conditions sampling according to a simple stopping rule yields an asymptotically normally distributed estimator which may be computed during the course of an epidemic. A small simulation study suggests that the asymptotic results applied to small samples yield accurate confidence intervals.

Suggested Citation

  • Huggins, R. M., 1992. "Fixed accuracy estimation for chain binomial models," Stochastic Processes and their Applications, Elsevier, vol. 41(2), pages 273-280, June.
    • Handle: RePEc:eee:spapps:v:41:y:1992:i:2:p:273-280
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