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.
Package details 


Maintainer  Ando Emerencia <[email protected]> 
License  MIT + file LICENSE 
Version  1.05 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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