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tsiR:An R package for time-series Susceptible-Infected-Recovered models ofepidemicsInformationregarding this package and a short tutorial can be found here:http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0185528Ifyou’ve found the package useful in your research, I ask that you citethe above PLOS ONE paper.Thispackage can be installed via CRAN. Updates to the package post the PLOSONE paper will follow below as they occur.

Note : 03/15/2019

Thiswarning message was added to V.0.4.1 but worth adding here as well – ifyou find very unreasonable reporting rates along either endpoints or inhighly variable epidemic regions using a gaussian regression, it may beworth reducing ‘sigmamax’ in either runtsir or estpars away from thedefault of 3 close to 0.5 or so.

Update V.0.4.1 : Minorupdate 01/29/2019

ThetsiR package has been updated to include further warning messages, bugfixes, and further annotations.

Update V.0.4.0 :Lyapunov Analysis 08/20/2018

ThetsiR package has been updated to include Global and Local LyapunovExponents. You can learn more and find examples of how to use thisfunction for the London data by typing ?TSIR_LE ?TSIR_LLE and ?plotLLEin the R console. This updateis now on CRAN.

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