README.Rmd

---
output: github_document
---

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```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# bsvars

Bayesian Estimation of Structural Vector Autoregressive Models

This package provides efficient algorithms for Bayesian estimation of Structural Vector Autoregressive (SVAR) models via Markov chain Monte Carlo methods. A wide range of SVAR models is considered, including homo- and heteroskedastic specifications and those with non-normal structural shocks.

# Installation

Just open your **R** and type:
```
install.packages("bsvars")
```

The package is under intensive development. To the the newest changes install it by typing:
```
devtools::install_git("https://github.com/donotdespair/bsvars.git")
```

# Start your Bayesian analysis of data

The beginnings are as easy as ABC:
```{r, eval=FALSE, echo=TRUE}
# upload the package
library(bsvars)

# upload data
data(us_fiscal_lsuw)
 
# specify the model and set seed
specification  = specify_bsvar_sv$new(us_fiscal_lsuw, p = 4)
set.seed(123)
 
# run the burn-in
burn_in        = estimate_bsvar_sv(1000, specification)

# estimate the model
posterior      = estimate_bsvar_sv(50000, burn_in$get_last_draw(), thin = 10)

# normalise the posterior
BB            = posterior$last_draw$starting_values$B      # get the last draw of B
B_hat         = diag(sign(diag(BB))) %*% BB                # set positive diagonal elements
normalise_posterior(posterior, B_hat)                      # draws in posterior are normalised

# Now, you're ready to analyse your model!
```

# Progress bar

MCMCs for multivariate dynamic structural models might take a while to run. **bsvars** relies on efficient algorithms and fast codes developed using **cpp** code via **Rcpp** and **RcppArmadillo** packages to cut the time of computations by orders of magnitude. Still, while waiting these a few minutes, you can track the progress by looking at the beautiful progress bar:

![bsvars::progress_bar](inst/varia/progress.png)

## License

This package is distributed under license GPL (>= 3)

Copyright `r knitr::asis_output("\U00A9")` 2022  Tomasz Woźniak (email: <wozniak.tom@pm.me>)

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