Package: EpiILM 1.5.2

Waleed Almutiry

EpiILM: Spatial and Network Based Individual Level Models for Epidemics

Provides tools for simulating from discrete-time individual level models for infectious disease data analysis. This epidemic model class contains spatial and contact-network based models with two disease types: Susceptible-Infectious (SI) and Susceptible-Infectious-Removed (SIR).

Authors:Vineetha Warriyar. K. V., Waleed Almutiry, and Rob Deardon

EpiILM_1.5.2.tar.gz
EpiILM_1.5.2.zip(r-4.5)EpiILM_1.5.2.zip(r-4.4)EpiILM_1.5.2.zip(r-4.3)
EpiILM_1.5.2.tgz(r-4.4-x86_64)EpiILM_1.5.2.tgz(r-4.4-arm64)EpiILM_1.5.2.tgz(r-4.3-x86_64)EpiILM_1.5.2.tgz(r-4.3-arm64)
EpiILM_1.5.2.tar.gz(r-4.5-noble)EpiILM_1.5.2.tar.gz(r-4.4-noble)
EpiILM_1.5.2.tgz(r-4.4-emscripten)
EpiILM.pdf |EpiILM.html
EpiILM/json (API)

# Install 'EpiILM' in R:
install.packages('EpiILM', repos = c('https://epiverse-connect.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/waleedalmutiry/epiilm/issues

Datasets:
  • tswv - Tomato Spotted Wilt Virus (TSWV) data

On CRAN:

4.80 score 6 stars 21 scripts 257 downloads 7 exports 8 dependencies

Last updated 4 years agofrom:a22caac0e2. Checks:OK: 7 NOTE: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-win-x86_64NOTENov 09 2024
R-4.5-linux-x86_64NOTENov 09 2024
R-4.4-win-x86_64OKNov 09 2024
R-4.4-mac-x86_64OKNov 09 2024
R-4.4-mac-aarch64OKNov 09 2024
R-4.3-win-x86_64OKNov 09 2024
R-4.3-mac-x86_64OKNov 09 2024
R-4.3-mac-aarch64OKNov 09 2024

Exports:as.epidataepiBR0epidataepidicepilikeepimcmcpred.epi

Dependencies:adaptMCMCcodaLaplacesDemonlatticeMatrixramcmcRcppRcppArmadillo

Posterior Predictive Forecasting and Model Assessment

Rendered fromPredict.Rnwusingutils::Sweaveon Nov 09 2024.

Last update: 2020-09-30
Started: 2020-02-23