Author: Emma Southall; Michael J. Tildesley; Louise Dyson
Title: Prospects for detecting early warning signals in discrete event sequence data: application to epidemiological incidence data Document date: 2020_4_2
ID: dp4qv77q_27
Snippet: where the integral approximation holds for ∆t sufficiently small. In the supporting 198 text (S2 Fig) we demonstrate that for our parameters, this approximation works well for 199 ∆t up to 3. We can derive EWS in disease incidence aggregated over a time interval ∆t 200 (e.g. daily, weekly, biweekly cases) using the well-known central moments of the Poisson 201 distribution:.....
Document: where the integral approximation holds for ∆t sufficiently small. In the supporting 198 text (S2 Fig) we demonstrate that for our parameters, this approximation works well for 199 ∆t up to 3. We can derive EWS in disease incidence aggregated over a time interval ∆t 200 (e.g. daily, weekly, biweekly cases) using the well-known central moments of the Poisson 201 distribution:
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