fastVAR: fastVAR
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.
| Version: |
1.2.1 |
| Depends: |
glmnet |
| Suggests: |
multicore |
| Published: |
2012-02-19 |
| Author: |
Jeffrey Wong |
| Maintainer: |
<jeff.ct.wong at stanford.edu> |
| License: |
GPL |
| NeedsCompilation: |
no |
| In views: |
TimeSeries |
| CRAN checks: |
fastVAR results |
Downloads: