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tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics

Author(s): Becker, Alexander D.; Grenfell, Bryan T.

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dc.contributor.authorBecker, Alexander D.-
dc.contributor.authorGrenfell, Bryan T.-
dc.date.accessioned2019-04-19T18:35:49Z-
dc.date.available2019-04-19T18:35:49Z-
dc.date.issued2017-09-28en_US
dc.identifier.citationBecker, Alexander D., Grenfell, Bryan T. (2017). tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics. PLOS ONE, 12 (9), e0185528 - e0185528. doi:10.1371/journal.pone.0185528en_US
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1n13w-
dc.description.abstracttsiR is an open source software package implemented in the R programming language designed to analyze infectious disease time-series data. The software extends a well-studied and widely-applied algorithm, the time-series Susceptible-Infected-Recovered (TSIR) model, to infer parameters from incidence data, such as contact seasonality, and to forward simulate the underlying mechanistic model. The tsiR package aggregates a number of different fitting features previously described in the literature in a user-friendly way, providing support for their broader adoption in infectious disease research. Also included in tsiR are a number of diagnostic tools to assess the fit of the TSIR model. This package should be useful for researchers analyzing incidence data for fully-immunizing infectious diseases.en_US
dc.format.extente0185528 - e0185528en_US
dc.language.isoen_USen_US
dc.relation.ispartofPLOS ONEen_US
dc.rightsFinal published version. This is an open access article.en_US
dc.titletsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemicsen_US
dc.typeJournal Articleen_US
dc.identifier.doidoi:10.1371/journal.pone.0185528-
dc.date.eissued2017-09-28en_US
dc.identifier.eissn1932-6203-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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