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ragt2ridges  

Ridge Estimation of Vector Auto-Regressive (VAR) Processes
View on CRAN: Click here


Download and install ragt2ridges package within the R console
Install from CRAN:
install.packages("ragt2ridges")

Install from Github:
library("remotes")
install_github("cran/ragt2ridges")

Install by package version:
library("remotes")
install_version("ragt2ridges", "0.3.4")



Attach the package and use:
library("ragt2ridges")
Maintained by
Wessel N. van Wieringen
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-05-10
Latest Update:
Description:
The ragt2ridges-package provides ridge maximum likelihood estimation of vector auto-regressive processes: the VAR(1), VAR(2) and VARX(1) model (more to be added). Prior knowledge may be incorporated in the estimation through a) specification of the edges believed to be absent in the time series chain graph, and b) a shrinkage target towards which the parameter estimate is shrunken for large penalty parameter values. Estimation functionality is accompanied by methodology for penalty parameter selection. In addition, the package offers supporting functionality for the exploitation of estimated models. Among others, i) a procedure to infer the support of the non-sparse ridge estimate (and thereby of the time series chain graph) is implemented, ii) a table of node-wise network summary statistics, iii) mutual information analysis, and iv) impulse response analysis. Cf. Miok et al. (2017) and Miok et al. (2019) for details on the implemented methods.
How to cite:
Wessel N. van Wieringen (2016). ragt2ridges: Ridge Estimation of Vector Auto-Regressive (VAR) Processes. R package version 0.3.4, https://cran.r-project.org/web/packages/ragt2ridges. Accessed 15 Jul. 2026.
Previous versions and publish date:
(2026-07-09 06:48), 0.1.9 (2016-05-10 15:10), 0.2.0 (2016-05-24 16:32), 0.2.1 (2016-08-26 20:35), 0.2.2 (2016-09-24 18:00), 0.2.3 (2016-10-12 23:59), 0.2.4 (2017-04-04 17:38), 0.3.0 (2017-11-10 23:28), 0.3.1 (2017-11-21 10:12), 0.3.2 (2018-12-20 14:00), 0.3.3 (2019-12-05 14:10), 0.3.4 (2020-01-28 16:30)
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