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.