Package: argo 3.0.2
Shihao Yang
argo: Accurate Estimation of Influenza Epidemics using Google Search Data
Augmented Regression with General Online data (ARGO) for accurate estimation of influenza epidemics in United States on national level, regional level and state level. It replicates the method introduced in paper Yang, S., Santillana, M. and Kou, S.C. (2015) <doi:10.1073/pnas.1515373112>; Ning, S., Yang, S. and Kou, S.C. (2019) <doi:10.1038/s41598-019-41559-6>; Yang, S., Ning, S. and Kou, S.C. (2021) <doi:10.1038/s41598-021-83084-5>.
Authors:
argo_3.0.2.tar.gz
argo_3.0.2.zip(r-4.5)argo_3.0.2.zip(r-4.4)argo_3.0.2.zip(r-4.3)
argo_3.0.2.tgz(r-4.4-any)argo_3.0.2.tgz(r-4.3-any)
argo_3.0.2.tar.gz(r-4.5-noble)argo_3.0.2.tar.gz(r-4.4-noble)
argo_3.0.2.tgz(r-4.4-emscripten)argo_3.0.2.tgz(r-4.3-emscripten)
argo.pdf |argo.html✨
argo/json (API)
| # Install 'argo' in R: |
| install.packages('argo', repos = c('https://epiverse-connect.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:cd77311a40. Checks:OK: 7. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 09 2024 |
| R-4.5-win | OK | Nov 09 2024 |
| R-4.5-linux | OK | Nov 09 2024 |
| R-4.4-win | OK | Nov 09 2024 |
| R-4.4-mac | OK | Nov 09 2024 |
| R-4.3-win | OK | Nov 09 2024 |
| R-4.3-mac | OK | Nov 09 2024 |
Exports:argoargo_mainargo2argo2_mainargox_mainboot_rebootstrap_relative_efficiencyheatmap_argoheatmap_corload_dataload_reg_datalogitlogit_invparse_gt_weeklyparse_unrevised_iliplot_argosummary_argo
Dependencies:bootcodetoolsforeachglmnetiteratorslatticeMatrixRcppRcppEigenshapesurvivalXMLxtablextszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Construct ARGO object | argo |
| main function for argo | argo_main |
| ARGO second step | argo2 |
| main function for argo2 | argo2_main |
| main function for argox | argox_main |
| wrapper for bootstrap relative efficiency confidence interval | boot_re |
| bootstrap relative efficiency confidence interval | bootstrap_relative_efficiency |
| Parsing each Google Trends file downloaded from Google Trends API | gt.parser.pub.api |
| Parsing each Google Trends file downloaded from website | gt.parser.pub.web |
| Heatmap plot of ARGO coefficients applied on CDC's ILI data | heatmap_argo |
| Heatmap plot of correlation matrix | heatmap_cor |
| Parsing of raw data | load_data |
| Parsing of raw data for regional ILI estimation | load_reg_data |
| logit function | logit |
| inverse logit function | logit_inv |
| Parsing of Google Trends data | parse_gt_weekly |
| Parsing of unrevised ili from online source | parse_unrevised_ili |
| Time series plot of ARGO applied on CDC's ILI data | plot_argo |
| performance summary of ARGO applied on CDC's ILI data | summary_argo |
