- Using an updated version of 
Rcpp to address an issue
with Rcpp::stop. 
stochvol_ocsn2007 can handle multi-column input. 
stochvol_ksc1998 can handle multi-column input. 
- Added 
post_gamma_state_variance for posterior
simulation of constant error variances of the state equation. 
- Added 
post_normal_covar_tvp for posterior simulation of
time varying, lower triangular covariance matrices. 
- Added 
post_normal_covar_const for posterior simulation
of constant, lower triangular covariance matrices. 
- Fixed alias issue resulting from use of 
roxygen2. 
- Made 
kalman_dk callable from C++. 
- Stochastic volatility algorithms allow to set the offsetting
constant manually.
 
- Changed 
stoch_vol to a wrapper for
stochvol_ksc1998. 
- Added stochastic volatility algorithm of Kim et al. (1998) in a
separate function 
stochvol_ksc1998. 
- Added stochastic volatility algorithm of Omori et al. (2007) in
function 
stochvol_ocsn2007. 
- Fixed bug with detection of deterministic terms in
bvar. 
- Implemented recursive iterations for forecasts in C++.
 
- Replaced erroneous 
| in C++ sampling functions by
||. 
- Addressed CRAN NOTE on CITATION file
 
- Addressed the CRAN NOTE “Specified C++11: please drop specification
unless essential” by dropping the specification from “src/Makevars”
 
- Improved the treatment of 
bvar and bvec
objects if Gibbs sampler fails. 
- Fix erroneous SUR-matrix generation for VEC models with r = 0 in
.bvecalg. 
- Fix bug in 
.bvecalg and .bvectvpalg with
the storing of posterior draws of beta. 
- Fix bug of 
predict.bvar, which could not handle only
VARX models with contemporaneous exogenous variables only. 
- Model plot functions support boxplots.
 
- Fix typos in documentation.
 
- Added functionality for the simulation of models with time varying
parameters, both for VAR and VEC models.
 
- Added functionality for the simulation of models with stochastic
volatility, both for VAR and VEC models.
 
- Added a plot function for classes 
bvar and
bvec for visual inspection of posterior draws. 
- Changed the generation of the output object in the Gibbs sampler
functions 
bvaralg and bvecalg to make them
more stable for especially large output. 
- Changed 
draw_posterior to a generic function and added
the corresponding methods for BVAR, BVEC and DFM input. 
- Changed 
irf and fevd to generic
functions. 
- Corrected typos in documentation.
 
thin_posterior methods were renamed to
thin and are now methods of coda::thin. 
- Function 
irf allows to specify the size of a
shock. 
- Fixed a bug in 
ssvs_prior concerning BVEC models. 
- Fixed a bug with the prior in the BVEC algorithm.
 
- Changed 
thin_posterior to a generic function and added
methods for BVAR, BVEC and dynamic factor model input. 
- Changed 
add_prior to a generic function and added
methods for BVAR, BVEC and dynamic factor model input. 
- Added funcionality to estimate dynamic factor models (DFM).
 
predict requires to specify an object of class
ts as input for argument exogen. 
- Additioal argument checks for 
add_priors methods. 
- Updated documentation in 
minnesota_prior and for
add_prior methods. 
- Using instead of \url in documentation
 
- Omitted package 
Matrix from “Imports”” in DESCRIPTION,
which caused a note in version 0.0.3. 
- Added function 
bvarpost for posterior simulation of
BVAR models. 
- Added function 
bvecpost for posterior simulation of
BVEC models. 
- Added function 
draw_posterior for estimation of
multiple models. 
- Fixed erroneous calculation of structural forecast error variance
decompositions.
 
- More specification checks and increased robustness against erroneous
model specificaions.
 
- Function 
fevd calculates FEVDs based on means of
posterior draws of FEVDs and not based on the means of the coefficient
draws. 
- Function 
bvar and summary.bvar can deal
with inclusion parameters. 
- Added funtion 
add_priors for easier construction of
prior matrices for multiple models. 
gen_var and gen_vec can produce multiple
models. 
- Changed all argument names of 
predict.bvar to lower
cases. 
- Changed all argument names of 
post_normal,
post_normal_sur, post_coint_kls and
post_coint_kls_sur to lower case letters. 
- Replaced output element in function 
ssvs from
V_i to v_i. 
- Refined function 
minnesota_prior and added additional
functionaliy. 
- Fixed error message when creating seasonal dummies with
gen_var and gen_vec. 
- New data set 
us_macrodata. 
- Added additional checks in 
gen_vec. 
- Added functions 
inclusion_prior for the calculation of
inclusion probability priors as used by bvs and
ssvs. 
- Added 
summary functions. 
- Fixed conversion and collection of exogenous regressors in
bvec_to_bvar. 
- Fixed detection of deterministic terms in
bvec_to_bvar. 
- Updated documentation in 
kalman_dk. 
irf contains a new argument
keep_draws. 
- Additional checks in 
post_normal,
post_normal_sur, post_coint_kls and
post_coint_kls_sur. 
- Adapt vignette 
bvec. 
- Added 
loglik_normal for the calculation of a
multivariate normal log-likelihood. 
- Updated vignette 
ssvs after the introduction of
function ssvs_prior. 
- Added 
ssvs_prior for the calculation of prior matrices
for the SSVS algorithm. 
- Added 
minnesota_prior for the calculation of the
Minnesota prior. 
- Use unsigned integers for indices in Cpp code to address warnings
during installation.
 
- Better error handling in 
irf. 
- In 
post_coint_kls_sur the prior matrix g_i
can be time varying. 
bvar and predict also work only with
deterministic terms, i.e. p can be zero. 
- Use SVD to obtain a draw of beta in 
post_coint_kls and
post_coint_kls_sur. 
predict allows for p = 1. 
- Add legend to 
plot.bvarfevd.