inv_sympd() by Armadillo inv() in C++ Kalman Filter to improve numerical robustness at a minor performance cost.summary.dfm: print method showed that model had AR(1) errors even though idio.ar1 = FALSE by default.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.
na.keep = TRUE to fitted.dfm. Setting na.keep = FALSE allows interpolation of data based on the DFM. Thanks @apoorvalal (#45).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).New default em.method = "auto", which uses "BM" if the data has any missing values and "DGR" otherwise.
Added vignette providing a walkthrough of the main features.
DFM(). The new name was inspired by the vars package.