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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Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Becker, Alexander D. | - |
dc.contributor.author | Grenfell, Bryan T. | - |
dc.date.accessioned | 2019-04-19T18:35:49Z | - |
dc.date.available | 2019-04-19T18:35:49Z | - |
dc.date.issued | 2017-09-28 | en_US |
dc.identifier.citation | Becker, 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.0185528 | en_US |
dc.identifier.uri | http://arks.princeton.edu/ark:/88435/pr1n13w | - |
dc.description.abstract | tsiR 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.extent | e0185528 - e0185528 | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartof | PLOS ONE | en_US |
dc.rights | Final published version. This is an open access article. | en_US |
dc.title | tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics | en_US |
dc.type | Journal Article | en_US |
dc.identifier.doi | doi:10.1371/journal.pone.0185528 | - |
dc.date.eissued | 2017-09-28 | en_US |
dc.identifier.eissn | 1932-6203 | - |
pu.type.symplectic | http://www.symplectic.co.uk/publications/atom-terms/1.0/journal-article | en_US |
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tsiR_An_R_package_2017.pdf | 1.37 MB | Adobe PDF | View/Download |
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