= Poisson working models for averaged counts
If $C_i\sim\operatorname{Poisson}(T_i\lambda_i)$ counts events over $T_i$ days, then the daily average $C_i/T_i$ has mean $\lambda_i$ and variance $\lambda_i/T_i$. It is not itself a Poisson variable unless $T_i=1$. Known observation periods allow count modelling with a log-exposure <offset>; otherwise <Quasi-Poisson regression> may be used as a working mean-variance model, with uncertainty qualified by the missing exposure information.
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