Package: EpiSoon 0.3.1

Sam Abbott

EpiSoon: Forecast Cases Using Reproduction Numbers

To forecast the time-varying reproduction number and use this to forecast reported case counts. Includes tools to evaluate a range of models across samples and time series using proper scoring rules.

Authors:Sam Abbott [aut, cre], Nikos Bosse [aut], Joel Hellewell [aut], Katharine Sherratt [aut], James Munday [aut], Robin Thompson [aut], Aurelien Chateigner [aut], Sylvain Mareschal [aut], Andrea Rau [aut], Nathalie Vialaneix [aut], Michael DeWitt [aut], Sebastian Funk [aut]

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EpiSoon.pdf |EpiSoon.html✨
EpiSoon/json (API)
NEWS

# Install 'EpiSoon' in R:

install.packages('EpiSoon', repos = c('https://epiforecasts.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/epiforecasts/episoon/issues

Datasets:

example_obs_cases - Example Observed Cases
example_obs_rts - Example Observed Rts
example_serial_interval - Example Serial Interval

On CRAN:

case-forecasts forecasts

28 exports 7 stars 1.58 score 63 dependencies 1 dependents

Last updated 1 years agofrom:d8eb427000

Exports:%>%brms_model bsts_model compare_models compare_timeseries draw_from_si_prob evaluate_model fable_model forecast_cases forecast_cases_directly forecast_model forecast_rt forecastHybrid_model iterative_case_forecast iterative_direct_case_forecast iterative_rt_forecast plot_compare_timeseries plot_forecast plot_forecast_evaluation plot_scores predict_cases predict_current_cases score_case_forecast score_forecast stackr_model summarise_case_forecast summarise_forecast summarise_scores

Dependencies:backports checkmate cli codetools colorspace cowplot cpp11 data.table digest dplyr evaluate fansi farver furrr future generics ggplot2 globals glue gtable HDInterval highr isoband knitr labeling lattice lifecycle listenv lubridate magrittr MASS Matrix Metrics mgcv munsell nlme parallelly pillar pkgconfig purrr R.methodsS3 R.oo R.utils R6 RColorBrewer Rcpp RcppArmadillo rlang scales scoringRules scoringutils stringi stringr tibble tidyr tidyselect timechange utf8 vctrs viridisLite withr xfun yaml

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
brms Model Wrapper	brms_model
bsts Model Wrapper	bsts_model
Compare forecasting models	compare_models
Compare timeseries and forecast models	compare_timeseries
Draw from the Serial Interval Probability Distribution	draw_from_si_prob
Evaluate a Model for Forecasting Rts	evaluate_model
Example Observed Cases	example_obs_cases
Example Observed Rts	example_obs_rts
Example Serial Interval	example_serial_interval
fable Model Wrapper	fable_model
Forecasts Cases for a Rt Forecasts	forecast_cases
Forecasts Cases Directly	forecast_cases_directly
forecast Model Wrapper	forecast_model
Fit and Forecast using a Model	forecast_rt
forecastHybrid Model Wrapper	forecastHybrid_model
Iteratively Forecast Cases Using an Iterative Rt Forecast	iterative_case_forecast
Iteratively forecast directly on cases	iterative_direct_case_forecast
Iteratively Forecast	iterative_rt_forecast
Summary plots to compare timeseries and forecast models	plot_compare_timeseries
Plot a Forecast	plot_forecast
Plot a Forecast	plot_forecast_evaluation
Plot forecast scores	plot_scores
Predict cases for a single Rt sample forecasts	predict_cases
Predict cases for Rts based on observed data	predict_current_cases
Score a case forecast	score_case_forecast
Score a Model Fit	score_forecast
Stack Models According to CRPS	stackr_model
Summarise Forecast Cases	summarise_case_forecast
Summarise Forecast Rts	summarise_forecast
Summarise model forecasting scores	summarise_scores

Package: EpiSoon 0.3.1

EpiSoon: Forecast Cases Using Reproduction Numbers

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