NEWS
sstvars 1.1.4
- Updates to the documentation
sstvars 1.1.3 (2025-01-30)
- Fixed a bug that prevented printing models that impose restrictions on the AR parameters.
- Now fitSTVAR normalizes the first row of the impact matrix B_1 to be positive and in a decreasing order also for skewed t models.
- Now swap_B_signs also swaps the signs of the appropriate skewness parameter values for skewed t models, so that the resulting model
is observationally equivalent to the original model.
- Increased the default maxit from 1000 to 2000 in fitSTVAR.
sstvars 1.1.2 (2025-01-08)
- 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.
sstvars 1.1.1 (2024-12-07)
- 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 1.1.0 (2024-11-29)
- 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 1.0.2
- Updated readme.
- Updated documentation.
sstvars 1.0.1 (2024-05-29)
- Updated configure script to fix an issue with the installation on Mac OS X.
sstvars 1.0.0 (2024-05-27)