Some developments on seasonal INAR processes with application to influenza data
Fatimah E Almuhayfith, Emmanuel W Okereke, Manik Awale, Hassan S Bakouch, Hana N Alqifari · 2023
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Description
Fatimah Almuhayfith and co-authors present a new model for seasonal disease counts in this 2023 paper. Flu data come in seasons, and weekly case counts often show too many zeros, too few zeros, or more spread than simple models allow. A model that handles all those traits at once was missing.
The team builds a flexible model for counts over time with a seasonal pattern built in. They set out its basic traits and test three ways of fitting its simpler one-step form on simulated data. The model is then applied to weekly flu data from one county in southwest Germany. It fit the real data better than existing models, the authors report.
Catalog record
| CREATOR | Fatimah E Almuhayfith, Emmanuel W Okereke, Manik Awale, Hassan S Bakouch, Hana N Alqifari |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 34 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |