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Spatiotemporal individual-level model of seasonal infectious disease transmission within the Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) framework are applied to model seasonal infectious disease transmission. This package employs a likelihood based Monte Carlo Expectation Conditional Maximization (MCECM) algorithm for estimating model parameters. In addition to model fitting and parameter estimation, the package offers functions for calculating AIC using real pandemic data and conducting simulation studies customized to user-specified model configurations.
Version: | 0.0.1 |
Depends: | R (≥ 3.5.0) |
Imports: | MASS, mvtnorm, ngspatial, stats |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2025-06-06 |
DOI: | 10.32614/CRAN.package.SeasEpi |
Author: | Amin Abed |
Maintainer: | Amin Abed <abeda at myumanitoba.ca> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | SeasEpi results |
Reference manual: | SeasEpi.pdf |
Package source: | SeasEpi_0.0.1.tar.gz |
Windows binaries: | r-devel: not available, r-release: SeasEpi_0.0.1.zip, r-oldrel: not available |
macOS binaries: | r-release (arm64): SeasEpi_0.0.1.tgz, r-oldrel (arm64): SeasEpi_0.0.1.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.