error_bands_irf

A function to estimate the confidence intervals for
irf and oirf.

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

error_bands_irf function

<dl><dt>v</dt>
<dd>a var object as from fitVAR or simulateVAR</dd>
<dt>irf</dt>
<dd>irf output from impulseResponse function</dd>
<dt>alpha</dt>
<dd>level of confidence (default <code>alpha = 0.01</code>)</dd>
<dt>m</dt>
<dd>number of bootstrapped series (default <code>m = 100</code>)</dd>
<dt>resampling</dt>
<dd>type of resampling: <code>"bootstrap"</code> or
<code>"jackknife"</code></dd>
<dt>...</dt>
<dd>some options for the estimation: <code>verbose = TRUE</code>
or <code>FALSE</code>, <code>mode = "fast"</code> or <code>"slow"</code>,
<code>threshold = TRUE</code> or <code>FALSE</code>.</dd></dl>

Arguments

Error bands for IRF — error_bands_irf

<dl>

<dt>v</dt>
<dd>a var object as from fitVAR or simulateVAR</dd>


<dt>irf</dt>
<dd>irf output from impulseResponse function</dd>


<dt>alpha</dt>
<dd>level of confidence (default <code>alpha = 0.01</code>)</dd>


<dt>m</dt>
<dd>number of bootstrapped series (default <code>m = 100</code>)</dd>


<dt>resampling</dt>
<dd>type of resampling: <code>"bootstrap"</code> or
<code>"jackknife"</code></dd>


<dt>...</dt>
<dd>some options for the estimation: <code>verbose = TRUE</code>
or <code>FALSE</code>, <code>mode = "fast"</code> or <code>"slow"</code>,
<code>threshold = TRUE</code> or <code>FALSE</code>.</dd>

</dl>

error_bands_irf: Error bands for IRF

Description

Usage

Value

Arguments