Package: BayesianFitForecast 1.1.0

Gerardo Chowell

BayesianFitForecast: Bayesian Parameter Estimation and Forecasting for Epidemiological Models

Methods for Bayesian parameter estimation and forecasting in epidemiological models. Functions enable model fitting using Bayesian methods and generate forecasts with uncertainty quantification. Implements approaches described in <doi:10.48550/arXiv.2411.05371> and <doi:10.1002/sim.9164>.

Authors:Hamed Karami [aut], Amanda Bleichrodt [aut], Ruiyan Luo [aut], Gerardo Chowell [aut, cre]

BayesianFitForecast_1.1.0.tar.gz
BayesianFitForecast_1.1.0.tar.gz(r-4.7-any)BayesianFitForecast_1.1.0.tar.gz(r-4.6-any)
BayesianFitForecast_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
BayesianFitForecast/json (API)

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

Bug tracker:https://github.com/gchowell/bayesianfitforecast/issues

Uses libs:
  • openjdk– OpenJDK Java runtime, using Hotspot JIT

On CRAN:

Conda:

openjdk

2.00 score 238 downloads 2 exports 69 dependencies

Last updated from:64f125dfcc. Checks:2 NOTE, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE307
source / vignettesOK213
linux-release-x86_64NOTE293
wasm-releaseOK157

Exports:Run_analyzeResultsRun_MCMC

Dependencies:abindbackportsbayesplotBHcallrcellrangercheckmateclicpp11crayondescdistributionaldplyrfarvergenericsggplot2ggridgesgluegridExtragtablehmsinlineisobandlabelinglifecycleloomagrittrmatrixStatsnumDerivopenxlsxotelpillarpkgbuildpkgconfigplyrposteriorprettyunitsprocessxprogresspspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreadxlrematchreshape2rJavarlangrstanS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithrxlsxxlsxjarszip

Getting Started with BayesianFitForecast

Rendered fromBayesianFitForecast.Rmdusingknitr::rmarkdownon Jun 19 2026.

Last update: 2024-12-05
Started: 2024-12-05