EpiILMCT: Continuous Time Distance-Based and Network-Based Individual Level Models for Epidemics

Provides tools for simulating from continuous-time individual level models of disease transmission, and carrying out infectious disease data analyses with the same models. The epidemic models considered are distance-based and/or contact network-based models within Susceptible-Infectious-Removed (SIR) or Susceptible-Infectious-Notified-Removed (SINR) compartmental frameworks. An overview of the implemented continuous-time individual level models for epidemics is given by Almutiry and Deardon (2019) <doi:10.1515/ijb-2017-0092>.

Version: 1.1.6
Depends: graphics, stats, utils, coda, parallel, R (≥ 3.5.0)
Imports: methods, igraph
Published: 2020-01-21
Author: Waleed Almutiry [aut, cre], Rob Deardon [aut, ths], Vineetha Warriyar K. V. [ctb]
Maintainer: Waleed Almutiry <wkmtierie at qu.edu.sa>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/waleedalmutiry/EpiILMCT/
NeedsCompilation: yes
CRAN checks: EpiILMCT results


Reference manual: EpiILMCT.pdf
Package source: EpiILMCT_1.1.6.tar.gz
Windows binaries: r-devel: EpiILMCT_1.1.6.zip, r-devel-UCRT: EpiILMCT_1.1.6.zip, r-release: EpiILMCT_1.1.6.zip, r-oldrel: EpiILMCT_1.1.6.zip
macOS binaries: r-release (arm64): EpiILMCT_1.1.6.tgz, r-release (x86_64): EpiILMCT_1.1.6.tgz, r-oldrel: EpiILMCT_1.1.6.tgz
Old sources: EpiILMCT archive


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