print.summary.desla

internal

Calculates the desparsified lasso as originally introduced in van de Geer et al. (2014) <doi:10.1214/14-AOS1221>, and provides inference suitable for high-dimensional time series, based on the long run covariance estimator in Adamek et al. (2020) <arXiv:2007.10952>. Also estimates high-dimensional local projections by the desparsified lasso, as described in Adamek et al. (2022) <arXiv:2209.03218>.

Robert Adamek

desla

Desparsified Lasso Inference for Time Series

Stephan Smeekes

Ines Wilms

print.summary.desla function

<dl><dt>x</dt>
<dd>a <code>desla</code> object.</dd>
<dt>digits</dt>
<dd>digits.</dd>
<dt>signif.stars</dt>
<dd>show stars of significance.</dd>
<dt>show_selected</dt>
<dd>upper bound for which to show the names of selected variables in the
lasso regressions (default is 10)</dd>
<dt>...</dt>
<dd>additional arguments (ignored).</dd></dl>

Arguments

Print desla summary output — print.summary.desla

<dl>

<dt>x</dt>
<dd>a <code>desla</code> object.</dd>


<dt>digits</dt>
<dd>digits.</dd>


<dt>signif.stars</dt>
<dd>show stars of significance.</dd>


<dt>show_selected</dt>
<dd>upper bound for which to show the names of selected variables in the
lasso regressions (default is 10)</dd>


<dt>...</dt>
<dd>additional arguments (ignored).</dd>

</dl>

print.summary.desla: Print desla summary output

Description

Usage

Arguments