- 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 withposteriorfirst 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
- Simplified the prior hierarchy for the shrinkage parameters of matrices \eqn{B} and \eqn{A} #24
- repo transferred from GitLab to GitHub
- repository is made public
- version to be premiered on CRAN
- 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
- 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!]