fastVAR (1.2.1)

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This package is designed for time series data. Fits Vector Autoregressive models and Vector Autoregressive models with Exogenous Inputs. For speedup, fastVAR can use multiple cpu cores to calculate the estimates. For very large systems, fastVAR uses Lasso penalty to return very sparse coefficient matrices. Regression diagnostics can be used to compare models, and prediction functions can be used to calculate the n-step ahead prediction. Faster implementations in C coming soon.

Maintainer: Unknown
Author(s): Jeffrey Wong

License: GPL

Uses: glmnet, multicore

Released almost 8 years ago.

2 previous versions



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