autovarCore: Automated Vector Autoregression Models and Networks

Automatically find the best vector autoregression models and networks for a given time series data set. 'AutovarCore' evaluates eight kinds of models: models with and without log transforming the data, lag 1 and lag 2 models, and models with and without weekday dummy variables. For each of these 8 model configurations, 'AutovarCore' evaluates all possible combinations for including outlier dummies (at 2.5x the standard deviation of the residuals) and retains the best model. Model evaluation includes the Eigenvalue stability test and a configurable set of residual tests. These eight models are further reduced to four models because 'AutovarCore' determines whether adding weekday dummies improves the model fit.

Version: 1.0-2
Imports: Rcpp (≥ 0.11.4), Amelia, jsonlite, parallel, stats, urca, vars
LinkingTo: Rcpp
Suggests: testthat, roxygen2
Published: 2018-01-29
Author: Ando Emerencia [aut, cre]
Maintainer: Ando Emerencia <ando.emerencia at>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README
In views: TimeSeries
CRAN checks: autovarCore results


Reference manual: autovarCore.pdf
Package source: autovarCore_1.0-2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X El Capitan binaries: r-release: autovarCore_1.0-2.tgz
OS X Mavericks binaries: r-oldrel: autovarCore_1.0-0.tgz
Old sources: autovarCore archive


Please use the canonical form to link to this page.