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 In views: TimeSeries CRAN checks: quadVAR results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=quadVAR to link to this page.
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