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This github repo is a companion to the article A hierarchical Bayesian implementation of a novel inverted generalized logistic growth curve for predicting diagnosed COVID-19 cases in 68 countries.

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bgautijonsson/isa_trans_covid19

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This github repo is a companion to the article A hierarchical Bayesian implementation of a novel inverted generalized logistic growth curve for predicting diagnosed COVID-19 cases in 68 countries currently under review for publishing at ISA Transactions.


The file Make_Past_Models.R is used to train the inverted generalized logistic growth model (IGLGM).

The files Analyze_Past_Models.R, Convergence_Info.R, Predict_Past_Models.R and Render_Summary_Document.R can be used to process model results after fitting.

There is also a shiny app in Past Models/Results/Model Checking/Interactive_Model_Checking.Rmd for interactive model checking and prediction.

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This github repo is a companion to the article A hierarchical Bayesian implementation of a novel inverted generalized logistic growth curve for predicting diagnosed COVID-19 cases in 68 countries.

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