RtForecastR: Real-Time Effective Reproduction Number Estimation and
Forecasting
Filtered (real-time/causal) and smoothed (retrospective)
estimation of the time-varying effective reproduction number (Rt)
from case-count time series, using the EpiFilter algorithm of
Parag (2021) <doi:10.1371/journal.pcbi.1009347>, together with a
one-step-ahead in-sample prediction check, a genuine out-of-sample
one-step forecast with predictive intervals, elimination
probability P(Rt < 1), and forecast calibration metrics (mean
absolute error, mean squared error, root mean squared error,
empirical coverage, and the weighted interval score of Bracher
et al. (2021) <doi:10.1371/journal.pcbi.1008618>).
Disease-agnostic: works for any pathogen given a known generation
interval.
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.5) |
| Imports: |
graphics, grDevices, stats, utils |
| Suggests: |
testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: |
2026-08-21 |
| DOI: |
10.32614/CRAN.package.RtForecastR |
| Author: |
Raj Subedi [aut, cre, cph] (Copyright holder for all files except
epiFilter.R, epiSmoother.R, and the original recursPredict.R logic
(see Kris V. Parag entry); author of R/recursPredict.R's
configurable-grid maxI extension and R/recursPredictQuantiles.R),
Kris V. Parag [ctb, cph] (Author/copyright holder of the original
EpiFilter algorithm (epiFilter, epiSmoother, recursPredict); files
R/epiFilter.R, R/epiSmoother.R and R/recursPredict.R are unmodified
or lightly modified ports of that work, released under GPL-3) |
| Maintainer: |
Raj Subedi <rajsubediresearch at gmail.com> |
| BugReports: |
https://github.com/rajsubediresearch/RtForecastR/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/rajsubediresearch/RtForecastR |
| NeedsCompilation: |
no |
| Language: |
en-US |
| Materials: |
NEWS |
| CRAN checks: |
RtForecastR results |
Documentation:
Downloads:
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