sstvars 1.0.0
sstvars 1.0.1
- Updated configure script to fix an issue with the installation on
Mac OS X.
sstvars 1.0.2
- Updated readme.
- Updated documentation.
sstvars 1.1.0
- MAJOR: Implemented independent skewed t distribution as a new
conditional distribution.
- MAJOR: Implemented a three phase estimation for TVAR models to
enhance computational efficiency.
- MAJOR: Implemented a possibility to maximize penalized
log-likelihood function that penalizes from unstable and
close-to-unstable estimates. Significantly improves the performance of
the estimation algorithm in some cases, particularly when the time
series are very persistent.
- Estimates not satisfying the usual stability condition for the
regimes can now be allowed.
- Adjusted the step sizes in finite difference numerical
differentiation.
- The step size in finite difference numerical differentiation can now
be adjusted in the function iterate_more.
- Changed the random parameter generation for ind_Student models
(estimation results with specific seeds are not backward
compatible).
- A new function: filter_estimates, which can be used considers
includes estimates that are not deemed inappropriate).
- A new function: plot_struct_shocks, which plots the structural shock
time series.
- A new function: stvar_to_sstvars110, which makes STVAR models
estimated with package versions <1.1.0 compatible with package
versions >=1.1.0.
- Some adjustments to estimation with fitSTVAR. NOTE: estimation
results with a particular seed may be different to the earlier
version.
- Removed the argument “filter_estimates” from fitSTVAR as a
redundancy (it is now always applied), since the function alt_stvar can
in any case be used to browse the estimates from any estimation
round.
- Added a new functionality to fitSSTVAR: structural models identified
by non-Gaussianity can be estimated based on different orderings or
signs of the columns of any of B_1,…,B_M (to conveniently examine models
corresponding to various orderings and signs in the presence of weak
identification with respect to ordering or signs of the columns of
B_2,…,B_M)
- FIXED A BUG in the simulation algorithm for models incorporating
independent Student’s t conditional distributions (the variance of each
structural shock was not scaled to one).
- FIXED A BUG in the GIRF simulation algorithm: the transition weights
were not necessarily high for ‘init_regime’ at impact (but the initial
values were generated from the correct regimes).
- Made the function profile_logliks more user friendly.
- Added a simplified table of contents to the vignette.
- The argument standard_error_print can now be used directly in the
summary-function to obtain printout of standard errors.
- Updated the documentation.
sstvars 1.1.1
- Now also the NLS step in the three-phase estimation estimation
checks that there are enough observations from each regime (previously
only LS estimation checked this).
- Added the argument min_obs_coef to fitSTVAR to let the user to
control the smallest accepted number of observations from each regime in
the LS/NLS step of the three-phase estimation. Also increased its
default value.
- Now alt_stvar, iterate_more, and filter_estimates retain
LS_estimates if the original model contains them.
- Now summary printout of class sstvar objects tells if the
log-likelihood function is penalized.
- Fixed CRAN check issues.
sstvars 1.1.2
- A new feature in GFEVD: initval_type = “data” and use_data_shocks =
TRUE now allows to filter the histories based on the dominance of a
specific regime.
- A new feature in GIRF: use_data_shocks, which allows to estimate the
GIRF using the length p histories in the data, using the shocks
recovered from the fitted model, with the possibility to filter the
histories based on the dominance of a specific regime as well as on the
sign and size of the shocks.
- GFEVDs are now calculated as the average over the GFEVDs based on
the different initial values (previously calculated based on the average
of the GIRFs based on the different initial values).
- Fixed the function stvar_to_sstvars110.
- Fixed a bug that caused GFEVD with data shocks to result in error
when using model estimate with package versions <1.1.0.
- Various small adjustments to printouts, documentation, etc.