Package: RtForecastR 0.1.1

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.

Authors:Raj Subedi [aut, cre, cph], Kris V. Parag [ctb, cph]