fit_vecm

A function to estimate a (possibly big)
multivariate VECM time series using penalized least squares
methods, such as ENET, SCAD or MC+.

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

fit_vecm function

<dl><dt>data</dt>
<dd>the data from the time series: variables
in columns and observations in rows</dd>
<dt>p</dt>
<dd>order of the VECM model</dd>
<dt>penalty</dt>
<dd>the penalty function to use.
Possible values are <code>"ENET"</code>, <code>"SCAD"</code> or <code>"MCP"</code></dd>
<dt>method</dt>
<dd><code>"cv"</code> or <code>"timeSlice"</code></dd>
<dt>log_scale</dt>
<dd>should the function consider the
<code>log</code> of the inputs? By default this is set to <code>TRUE</code></dd>
<dt>...</dt>
<dd>options for the function (TODO: specify)</dd></dl>

Arguments

Multivariate VECM estimation — fit_vecm

<dl>

<dt>data</dt>
<dd>the data from the time series: variables
in columns and observations in rows</dd>


<dt>p</dt>
<dd>order of the VECM model</dd>


<dt>penalty</dt>
<dd>the penalty function to use.
Possible values are <code>"ENET"</code>, <code>"SCAD"</code> or <code>"MCP"</code></dd>


<dt>method</dt>
<dd><code>"cv"</code> or <code>"timeSlice"</code></dd>


<dt>log_scale</dt>
<dd>should the function consider the
<code>log</code> of the inputs? By default this is set to <code>TRUE</code></dd>


<dt>...</dt>
<dd>options for the function (TODO: specify)</dd>

</dl>

fit_vecm: Multivariate VECM estimation

Description

Usage

Value

Arguments