الفهرس 
Title : Study for Tweedie Regression Model with Applications
ContentsOnly 14 pages are availabe for public view
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Abstract
Statistical distributions have been prominent in characterizing real-world events in recent years. new statistical distributions will be developed when undertaking in-deaths study on statistical distribution theory, and people will continue to be interested in constructing more flexible statistical distributions because of their utility. there have been many different types of generalized model distributions introduced and used for COVID-19 virus occurrences. The existence of additional parameters in these generalized model distributions is a regular occurrence.
This thesis aims to model the daily cases of the new corona virus deaths in Egypt using Tweedie regression models, Poisson regression and invars gaussian regression aiming to construct the confirmed and active regression cases, where and its impact on the number of deaths of the new Corona virus in Egypt, then the study data was extracted from the daily update of Corona virus cases issued by the Egypt Center for Diseases, the online control database, from January 1, 2021 to November 30, 2021.
Data were extracted to estimate the parameters of the regression models using the SPSS statistical program and the graphs from the MATLAB program, then the best regression model was selected through the quality criteria selection test. -2Log, AIC, BIC, then the results revealed that Tweedie model is the best in capturing excessive dispersal due to the large data size, and it is the best models for containing confirmed, active, and critical cases of Corona virus for daily cases in Egypt.