Mixed-Frequency Bayesian VAR Models
Overview
Functions and tools for estimation of mixed-frequency Bayesian vector autoregressive (VAR) models. The package implements a state space-based VAR model that handles mixed frequencies of the data as proposed by Schorfheide and Song (2015) doi:10.1080/07350015.2014.954707, and extensions thereof developed by Ankargren, Unosson and Yang (2020) doi:10.1515/jtse-2018-0034, Ankargren and Joneus (2019) arXiv:1912.02231, and Ankargren and Joneus (2020) doi:10.1016/j.ecosta.2020.05.007. The models are estimated using Markov Chain Monte Carlo to numerically approximate the posterior distribution. Prior distributions that can be used include normal-inverse Wishart and normal-diffuse priors as well as steady-state priors. Stochastic volatility can be handled by common or factor stochastic volatility models.
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- Enabled use of weekly-monthly frequency mix
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- Help pages
- 16includes a package overview page
- Examples that run
- 100%10 run in a plain check
- Exported functions with examples
- 80%
- Documented parameters
- 96%
- Return-value docs
- 100%
- Help pages citing references
- 25%
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People & History
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- RR 4.3.0 released · 2023-04-21
- archivedRemoved from CRAN2022-08-08issues were not corrected in time
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- unarchivedReturned to CRAN2021-02-10
- 0.5.62021-02-10 · diff ↗
- archivedRemoved from CRAN2021-02-05check problems were not corrected in time
- 0.5.4
- RR 4.0.0 released · 2020-04-24
- 0.5.32020-03-19 · diff ↗
- 0.5.22020-01-09 · diff ↗
- 0.5.1
- RR 3.6.0 released · 2019-04-26
- 0.4.02018-12-27
- RR 3.5.0 released · 2018-04-23
Package metadata
- First published
- 2018-12-27
- Total releases
- 6 / 8 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 12 KB / 2 files
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