dfms version 0.3.2

• Minor internal C++ changes to ensure compatibility with RcppArmadillo 15.0.2.

dfms version 0.3.1

• Fixed bug which occurred with only one quarterly variable (#73). Thanks @SantiagoD999 for reporting.

dfms version 0.3.0

• Added argument quarterly.vars, enabling mixed-frequency estimation with monthly and quarterly data following Banbura and Modugno (2014). The data matrix should contain the quarterly variables at the end (after the monthly ones).

dfms version 0.2.2

• Replaced Armadillo inv_sympd() by Armadillo inv() in C++ Kalman Filter to improve numerical robustness at a minor performance cost.

dfms version 0.2.1

• Fixed print bug in summary.dfm: print method showed that model had AR(1) errors even though idio.ar1 = FALSE by default.

dfms version 0.2.0

• Added argument idio.ar1 = TRUE allowing estimation of approximate DFM's with AR(1) observation errors.

• Added a small theoretical vignette entitled 'Dynamic Factor Models: A Very Short Introduction'. This vignette lays a foundation for the present and future functionality of dfms. I plan to implement all features described in this vignette until summer 2023.

dfms version 0.1.4

• Fixed minor bug in summary.dfm occurring if only one factor was estimated (basically an issue with dropping matrix dimensions which lead the factor summary statistics to be displayed without names).

dfms version 0.1.3

First official release of dfms on CRAN and GitHub.