tsiR: An R package for time-series Susceptible-Infected-Recovered models of epidemics
Author(s): Becker, Alexander D.; Grenfell, Bryan T.
DownloadTo refer to this page use:
http://arks.princeton.edu/ark:/88435/pr1n13w
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. |
Publication Date: | 28-Sep-2017 |
Electronic Publication Date: | 28-Sep-2017 |
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 |
DOI: | doi:10.1371/journal.pone.0185528 |
EISSN: | 1932-6203 |
Pages: | e0185528 - e0185528 |
Type of Material: | Journal Article |
Journal/Proceeding Title: | PLOS ONE |
Version: | Final published version. This is an open access article. |
Items in OAR@Princeton are protected by copyright, with all rights reserved, unless otherwise indicated.