Bridging Data Frequencies for Timely Economic Forecasts

Implements bridge and MIDAS-style mixed-frequency models for nowcasting and forecasting macroeconomic variables by linking higher-frequency indicator variables to a lower-frequency target series. The package standardizes input data, infers regular frequencies, forecasts missing indicator observations, and aggregates indicators to the target frequency before fitting a regression with autoregressive target dynamics. Frequency alignment can be customized through user-supplied conversion rules. For more on bridge and MIDAS models, see Baffigi, A., Golinelli, R., & Parigi, G. (2004) , Ghysels, Sinko, & Valkanov (2007) , Andreou, Ghysels, & Kourtellos (2010) , Schumacher (2016) , and Burri (2026) .


Reference manual

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install.packages("bridgr")

1.0.0 by Marc Burri, a month ago


https://github.com/marcburri/bridgr, https://marcburri.github.io/bridgr/


Report a bug at https://github.com/marcburri/bridgr/issues


Browse source code at https://github.com/cran/bridgr


Authors: Marc Burri [aut, cre, cph] (ORCID:


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dplyr, forecast, ggplot2, lifecycle, lubridate, rlang, scales, tsbox, withr

Suggests knitr, rmarkdown, srr, testthat


See at CRAN