dfms is now part of rOpenSci – following completion of a scientific review by @eeholmes and @santikka. This means the repo shifted to ropensci/dfms and the docs (now in rOpenSci style) to docs.ropensci.org/dfms.

Added a news() function for news decomposition identifying the contribution of new data releases to DFM predictions/nowcasts following research codes by Banbura and Modugno (2014). It supports efficient multi-target news estimation, has been tested with MQ/AR(1) model versions, and is suitable for mixed-frequency nowcasting applications.

Added arguments save.full.state to DFM() and use.full.state to predict(), fitted(), and residuals() - default TRUE. Full-state output includes idiosyncratic components (when modeled with idio.ar1 = TRUE). This generally improves the accuracy of DFM forecasts, but changes the interpretation for residuals/fitted values,
which are then no longer a function of the factors alone.

Marked 1.0.0 as the package is now peer-reviewed and feature-complete within the intended scope: the full and efficient implementation of Banbura and Modugno (2014) in R.