CRAN/E | ragt2ridges

ragt2ridges

Ridge Estimation of Vector Auto-Regressive (VAR) Processes

Installation

About

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) doi:10.1002/bimj.201500269 and Miok et al. (2019) doi:10.1002/bimj.201700195 for details on the implemented methods.

Citation ragt2ridges citation info
github.com/wvanwie/ragt2ridges

Key Metrics

Version 0.3.4
R ≥ 2.15.1
Published 2020-01-28 1547 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks ragt2ridges results

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Maintainer

Maintainer

Wessel N. van Wieringen

w.vanwieringen@vumc.nl

Authors

Wessel N. van Wieringen

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

ragt2ridges archive

Depends

R ≥ 2.15.1
igraph
rags2ridges

Imports

abind
expm
fdrtool
graphics
grDevices
MASS
Matrix
methods
mvtnorm
stats
Biobase
CGHbase

LinkingTo

Rcpp
RcppArmadillo

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