Packaged: 2021-09-15 21:46:00 UTC; ryanpeterson

Packaged: 2022-06-13 20:25:39 UTC; ryanpeterson

Title: Burden Estimate of Common Communicable Diseases in Settlements
Authors@R: person("You", "Li", email = "You.Li2@ed.ac.uk", role = c("aut", "cre"))
Description: Provides a practical tool for estimating the burden of common communicable diseases in settlements of displaced populations. An online version of the tool can be found at <http://who-refugee-bod.ecdf.ed.ac.uk/shiny/app/>. Estimates of burden of disease aim to synthesize data about cause-specific morbidity and mortality through a systematic approach that enables evidence-based decisions and comparisons across settings. The focus of this tool is on four acute communicable diseases and syndromes, including Acute respiratory infections, Acute diarrheal diseases, Acute jaundice syndrome and Acute febrile illnesses.
Imports: shiny, shinythemes, shinydashboard, shinyWidgets, shinyBS,
shinyjs, tidyr, dplyr, readxl, ggplot2, rlist, DT, stringr

Description: Best subset glm using AIC, BIC, EBIC, BICq or
Cross-Validation. For the normal case, the 'leaps' is used.
Otherwise, a slower exhaustive search. The 'xtable' package is
needed for vignette 'SimExperimentBICq.Rnw' accompanying this

Depends: R (>= 2.0.0), leaps, lars, ElemStatLearn
Description: Best subset glm using AIC, BIC, EBIC, BICq or Cross-Validation. For the normal case, the 'leaps' is used. Otherwise, a slower exhaustive search. The 'xtable' package is needed for vignette 'SimExperimentBICq.Rnw' accompanying this package.

Packaged: 2017-02-06 01:39:31 UTC; IanMcLeod

Description: Best subset glm using information criteria or cross-validation.
Packaged: 2017-02-23 17:54:29 UTC; IanMcLeod

Title: Best Subset GLM and Regression Utilities
Description: Best subset glm using information criteria or cross-validation. Implements PCR and PLS using AIC/BIC. Implements one-standard deviation rule for use with the `caret` package.

Author: A.I. McLeod, Changjiang Xu and Yuanhao Lai
Description: Best subset glm using information criteria or cross-validation,
carried by using 'leaps' algorithm (Furnival and Wilson, 1974) <doi:10.2307/1267601>
Implements one-standard deviation rule for use with the 'caret' package.