test_granger

This function should retain only the coefficients of the
matrices of the VAR that are statistically significative (from the bootstrap)

A wrapper for sparse VAR (Vector Autoregression) and
VECM (Vector Error Correction Model) time series models estimation
using penalties like ENET (Elastic Net), SCAD (Smoothly Clipped
Absolute Deviation) and MCP (Minimax Concave Penalty).
Based on the work of Basu and Michailidis (2015)
<doi:10.1214/15-AOS1315>.

Simone Vazzoler

sparsevar

Sparse VAR (Vector Autoregression) / VECM (Vector Error
Correction Model) Estimation

test_granger function

<dl><dt>v</dt>
<dd>the VAR object as from fitVAR or simulateVAR</dd>
<dt>eb</dt>
<dd>the error bands as obtained from errorBands</dd></dl>

Arguments

Test for Ganger Causality — test_granger

<dl>

<dt>v</dt>
<dd>the VAR object as from fitVAR or simulateVAR</dd>


<dt>eb</dt>
<dd>the error bands as obtained from errorBands</dd>

</dl>

test_granger: Test for Ganger Causality

Description

Usage

Value

Arguments