README.Rmd

---
output: github_document
---

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

# bsvarTVPs

Bayesian Structural Vector Autoregressions with Time-Varying Identification

Efficient algorithms for Bayesian estimation of Structural Vector Autoregressions (VARs) with Stochastic Volatility heteroskedasticity, Markov-switching and Time-Varying Identification of the Structural Matrix, and a three-level global-local hierarchical prior shrinkage for the structural and autoregressive matrices. The models were developed for a paper by [Camehl & Woźniak (2023)](https://doi.org/10.48550/arXiv.2311.05883). The 'bsvarTVPs' package is aligned regarding objects, workflows, and code structure with the R packages 'bsvars' by [Woźniak (2024)](https://doi.org/10.32614/CRAN.package.bsvars) and 'bsvarSIGNs' by [Wang & Woźniak (2024)](https://doi.org/10.32614/CRAN.package.bsvarSIGNs), and they constitute an integrated toolset.

# Installation

To install the **bsvarTVPs** package just type in **R**:
```
devtools::install_github("bsvars/bsvarTVPs")
```

# Checks

[![R-CMD-check](https://github.com/bsvars/bsvarTVPs/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/bsvars/bsvarTVPs/actions/workflows/R-CMD-check.yaml)