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BGVAR  

Bayesian Global Vector Autoregressions
View on CRAN: Click here


Download and install BGVAR package within the R console
Install from CRAN:
install.packages("BGVAR")

Install from Github:
library("remotes")
install_github("cran/BGVAR")

Install by package version:
library("remotes")
install_version("BGVAR", "2.5.8")



Attach the package and use:
library("BGVAR")
Maintained by
Maximilian Boeck
[Scholar Profile | Author Map]
First Published: 2020-06-19
Latest Update: 2023-12-13
Description:
Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 . Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available. The package has a companion paper: Boeck, M., Feldkircher, M. and F. Huber (2022) "BGVAR: Bayesian Global Vector Autoregressions with Shrinkage Priors in R", Journal of Statistical Software, Vol. 104(9), pp. 1-28 .
How to cite:
Maximilian Boeck (2020). BGVAR: Bayesian Global Vector Autoregressions. R package version 2.5.8, https://cran.r-project.org/web/packages/BGVAR. Accessed 01 May. 2025.
Previous versions and publish date:
2.0.0 (2020-06-19 13:10), 2.0.1 (2020-06-24 14:10), 2.1.0 (2020-09-07 14:50), 2.1.1 (2020-09-07 23:50), 2.1.2 (2020-09-14 23:40), 2.1.3 (2020-09-30 20:20), 2.1.4 (2020-11-14 15:50), 2.1.5 (2020-11-15 18:10), 2.2.0 (2021-05-03 11:10), 2.2.3 (2021-07-17 12:10), 2.2.4 (2021-07-20 09:20), 2.3.0 (2021-08-10 12:20), 2.3.1 (2021-09-10 11:10), 2.4.0 (2021-10-06 11:00), 2.4.1 (2021-11-04 09:10), 2.4.2 (2021-11-04 15:30), 2.4.3 (2021-11-06 16:00), 2.4.4 (2022-04-01 12:40), 2.4.5 (2022-04-04 12:50), 2.4.6 (2022-04-12 09:22), 2.5.0 (2022-05-02 11:40), 2.5.1 (2022-09-03 01:00), 2.5.2 (2022-10-26 17:27), 2.5.3 (2023-12-09 00:40), 2.5.4 (2023-12-11 09:00), 2.5.5 (2023-12-13 23:30), 2.5.6 (2024-07-03 19:20), 2.5.7 (2024-07-07 16:50)
Other packages that cited BGVAR R package
View BGVAR citation profile
Other R packages that BGVAR depends, imports, suggests or enhances
Complete documentation for BGVAR
Functions, R codes and Examples using the BGVAR R package
Some associated functions: BGVAR-package . add_shockinfo . avg.pair.cc . bgvar . coef . conv.diag . dic . eerData . excel_to_list . fevd . fitted . get_shockinfo . gfevd . hd . irf . list_to_matrix . logLik . lps . matrix_to_list . monthlyData . pesaranData . plot . predict . resid.corr.test . residuals . rmse . summary . testdata . vcov . 
Some associated R codes: BGVAR.R . RcppExports.R . bgvar-package.R . fevd.R . hd.R . helpers.R . irf.R . plot.R . predict.R . utils.R . zzz.R .  Full BGVAR package functions and examples
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