Package: SeasEpi 0.0.3

SeasEpi: Spatiotemporal Modeling of Seasonal Infectious Disease

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.

Authors:Amin Abed [aut, cre, cph], Mahmoud Torabi [ths], Zeinab Mashreghi [ths]

SeasEpi_0.0.3.tar.gz
SeasEpi_0.0.3.zip(r-4.7-any)SeasEpi_0.0.3.zip(r-4.6-any)SeasEpi_0.0.3.zip(r-4.5-any)
SeasEpi_0.0.3.tgz(r-4.6-any)SeasEpi_0.0.3.tgz(r-4.5-any)
SeasEpi_0.0.3.tar.gz(r-4.7-any)SeasEpi_0.0.3.tar.gz(r-4.6-any)
SeasEpi_0.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
SeasEpi/json (API)

# Install 'SeasEpi' in R:
install.packages('SeasEpi', repos = c('https://amin-abed.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 249 downloads 2 exports 6 dependencies

Last updated from:0f18d27bcf. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK116
source / vignettesOK172
linux-releaseOK98
macos-releaseOK240
macos-oldrelOK175
windows-develOK59
windows-releaseOK70
windows-oldrelOK73
wasm-releaseOK92

Exports:SeasEpi_Par_EstSeasEpi_Sim_Par_Est

Dependencies:batchmeansMASSmvtnormngspatialRcppRcppArmadillo

Readme and manuals

Help Manual

Help pageTopics
Hypothetical Datasetsadjacency_matrix data
SeasEpi for Real DataSeasEpi_Par_Est
SeasEpi for a Simulation StudySeasEpi_Sim_Par_Est