Running examples in 'bsvars-Ex.R' failed
The error most likely occurred in:

> ### Name: compute_variance_decompositions.PosteriorBSVARMIX
> ### Title: Computes posterior draws of the forecast error variance
> ###   decomposition
> ### Aliases: compute_variance_decompositions.PosteriorBSVARMIX
> 
> ### ** Examples
> 
> # upload data
> data(us_fiscal_lsuw)
> 
> # specify the model and set seed
> set.seed(123)
> specification  = specify_bsvar_mix$new(us_fiscal_lsuw, p = 1, M = 2)
The identification is set to the default option of lower-triangular structural matrix.
> 
> # run the burn-in
> burn_in        = estimate(specification, 10)
**************************************************|
bsvars: Bayesian Structural Vector Autoregressions|
**************************************************|
 Gibbs sampler for the SVAR-finiteMIX model             |
**************************************************|
 Progress of the MCMC simulation for 10 draws
    Every draw is saved via MCMC thinning
 Press Esc to interrupt the computations
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
> 
> # estimate the model
> posterior      = estimate(burn_in, 20)
**************************************************|
bsvars: Bayesian Structural Vector Autoregressions|
**************************************************|
 Gibbs sampler for the SVAR-finiteMIX model             |
**************************************************|
 Progress of the MCMC simulation for 20 draws
    Every draw is saved via MCMC thinning
 Press Esc to interrupt the computations
**************************************************|
0%   10   20   30   40   50   60   70   80   90   100%
[----|----|----|----|----|----|----|----|----|----|
**************************************************|
> 
> # compute forecast error variance decomposition 2 years ahead
> fevd           = compute_variance_decompositions(posterior, horizon = 8)