bvhar (version 2.2.2)

bvhar-package: bvhar: Bayesian Vector Heterogeneous Autoregressive Modeling

Description

Tools to model and forecast multivariate time series including Bayesian Vector heterogeneous autoregressive (VHAR) model by Kim & Baek (2023) (tools:::Rd_expr_doi("10.1080/00949655.2023.2281644")). 'bvhar' can model Vector Autoregressive (VAR), VHAR, Bayesian VAR (BVAR), and Bayesian VHAR (BVHAR) models.

Author

Maintainer: Young Geun Kim (ORCID) [copyright holder]

Other contributors:

• Changryong Baek [contributor]

Details

The bvhar package provides function to analyze and forecast multivariate time series data via vector autoregressive modeling. Here, vector autoregressive modelling includes:

• Vector autoregressive (VAR) model: var_lm()

• Vector heterogeneous autoregressive (VHAR) model: vhar_lm()

• Bayesian VAR (BVAR) model: var_bayes()

• Bayesian VHAR (BVHAR) model: vhar_bayes()

References

Kim, Y. G., and Baek, C. (2024). Bayesian vector heterogeneous autoregressive modeling. Journal of Statistical Computation and Simulation, 94(6), 1139-1157.

Kim, Y. G., and Baek, C. (n.d.). Working paper.

See Also

Useful links:

• https://ygeunkim.github.io/package/bvhar/

• https://github.com/ygeunkim/bvhar

• Report bugs at https://github.com/ygeunkim/bvhar/issues