Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015). Allows for the computation of impulse responses and forecasts and provides functionality for assessing results.
Functions to prepare and visualise tidy objects from BVAR.
Building a vector autoregressive model with R. My coursework for the course Time Series Analysis II (offered by University of Helsinki's Master's Programme in Mathematics and Statistics), spring 2020.
A lecture on Bayesian Vector Autoregressions using the bsvarSIGNs package given to Bayesian Econometrics students at the unimelb in October 2024
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