Long Term Prediction for Epidemic and Pandemic Data

Implementation of the methodology described in < http://est.ufmg.br/covidlp/home/pt/> which can be also found in help(models). Implemented models are currently the Poisson distribution. The mean function can be the basic generalized logistic form, or the seasonal effect which has under- or over-reporting effects in up to three weekdays, or the two curves form. Bayesian inference is made available through the 'stan' software and its diagnostic functions pool can be used. Plot methods are implemented to mimic the graphics from the 'shiny' app in the URL using the 'plotly' library.


Reference manual

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1.1.1 by Guido Alberti Moreira, 19 days ago

< http://est.ufmg.br/covidlp/home/pt/>

Browse source code at https://github.com/cran/PandemicLP

Authors: Débora de Freitas Magalhães [aut] , Marta Cristina Colozza Bianchi da Costa [aut] , Guido Alberti Moreira [cre, aut] , Thais Pacheco Menezes [aut] , Marcos Oliveira Prates [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports utils, methods, Rcpp, plotly, dplyr, curl, tidyr, covid19br

Depends on rstan, rstantools, stats

Suggests knitr, rmarkdown, webshot

Linking to BH, Rcpp, RcppEigen, RcppParallel, rstan, StanHeaders

System requirements: GNU make

See at CRAN