quadVAR: Quadratic Vector Autoregression
Estimate quadratic vector autoregression models with the
strong hierarchy using the Regularization Algorithm under Marginality
Principle (RAMP) by Hao et al. (2018)
<doi:10.1080/01621459.2016.1264956>, compare the performance with
linear models, and construct networks with partial derivatives.
Version: |
0.1.2 |
Imports: |
cli, dplyr, ggplot2, magrittr, ncvreg, qgraph, RAMP, rlang, shiny, shinythemes, stats, stringr, tibble, tidyr |
Suggests: |
nonlinearTseries, remotes, SIS, testthat (≥ 3.0.0) |
Published: |
2025-02-11 |
DOI: |
10.32614/CRAN.package.quadVAR |
Author: |
Jingmeng Cui
[aut, cre] |
Maintainer: |
Jingmeng Cui <jingmeng.cui at outlook.com> |
BugReports: |
https://github.com/Sciurus365/quadVAR/issues |
License: |
GPL (≥ 3) |
URL: |
https://github.com/Sciurus365/quadVAR,
https://sciurus365.github.io/quadVAR/ |
NeedsCompilation: |
no |
Materials: |
README NEWS |
CRAN checks: |
quadVAR results |
Documentation:
Downloads:
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