bsvars 2.1.0
Published on 11 December 2023
- Included Bayesian procedure for verifying structural shocks’ heteroskedastiicty equation-by-equation using Savage-Dickey density ratios #26
- Included Bayesian procedure for verifying joint hypotheses on autoregressive parameters using Savage-Dickey density ratios #26
- Included the possibility of specifying exogenous variables or deterministic terms and included the deterministic terms used by Lütkepohl, Shang, Uzeda, Woźniak (2023) #45
- Updated the data as in Lütkepohl, Shang, Uzeda, Woźniak (2023) #45
- Fixing the compilation problems reported HERE #48
- The package has its pkgdown website at bsvars.github.io/bsvars/ #38
The package is under intensive development, and more functionality will be provided soon! To see the package ROADMAP towards the next version 2.1.0.
Have a question, or suggestion, or wanna get in touch? Join the package DISCUSSION forum.
bsvars 2.0.0
Published on 23 October 2023
- Included Imports from package stochvol
- Posterior computations for:
- impulse responses and forecast error variance decomposition #3,
- structural shocks and historical decompositions #14
- fitted values #17
- conditional standard deviations #16
- regime probabilities for MS and MIX models #18
- Implemented faster samplers based on random number generators from armadillo via RcppArmadillo #7
- The
estimate_bsvar*
functions now also normalise the output w.r.t. to a structural matrix with positive elements on the main diagonal #9
- Changed the order of arguments in the
estimate_bsvar*
functions with posterior
first to facilitate workflows using the pipe |>
#10
- Include citation info for the package #12
- Corrected sampler for AR parameter of the SV equations #19
- Added samplers from joint predictive densities #15
- A new centred Stochastic Volatility heteroskedastic process is implemented #22
- Introduced a three-level local-global equation-specific prior shrinkage hierarchy for the parameters of matrices and #34
- Improved checks for correct specification of arguments
S
and thin
of the estimate
method as enquired by [@mfaragd](https://github.com/mfaragd) #33
- Improved the ordinal numerals presentation for thinning in the progress bar #27
bsvars 1.0.0
Published on 1 September 2022
- repo transferred from GitLab to GitHub
- repository is made public
- version to be premiered on CRAN
bsvars 0.0.2.9000
- Added a new progress bar for the
estimate_bsvar*
functions
- Developed R6 classes for model specification and posterior outcomes; model specification includes sub-classes for priors, identifying restrictions, data matrices, and starting values
- Added a complete package documentation
- Written help files
- Developed tests for MCMC reproducibility
- Included sample data
bsvars 0.0.1.9000
- cpp scripts are imported, compile, and give no Errors, Warnings, or Notes
- R wrappers for the functions are fully operating
- full documentation describing package and functions’ functionality [sic!]