fastridge

A wrapper around <code>fastridgeCpp</code>, for faster computation of the analytical solution for
ridge regression.

A set of tools that enables efficient estimation of penalized
Poisson Pseudo Maximum Likelihood regressions, using lasso or ridge penalties, for models
that feature one or more sets of high-dimensional fixed effects. The methodology is based on
Breinlich, Corradi, Rocha, Ruta, Santos Silva, and Zylkin (2021) <http://hdl.handle.net/10986/35451>
and takes advantage of the method of alternating projections of Gaure (2013)
<doi:10.1016/j.csda.2013.03.024> for dealing with HDFE, as well as
the coordinate descent algorithm of Friedman, Hastie and Tibshirani (2010)
<doi:10.18637/jss.v033.i01> for fitting lasso regressions. The package is also able to carry out
cross-validation and to implement the plugin lasso of Belloni, Chernozhukov, Hansen and Kozbur (2016)
<doi:10.1080/07350015.2015.1102733>.

Joao Cruz

penppml

Penalized Poisson Pseudo Maximum Likelihood Regression

Diego Ferreras Garrucho

Tom Zylkin

Nicolas Apfel

fastridge function

<dl><dt>x</dt>
<dd>Regressor matrix.</dd>
<dt>y</dt>
<dd>Dependent variable (a numeric vector).</dd>
<dt>weights</dt>
<dd>Vector of weights.</dd>
<dt>lambda</dt>
<dd>Penalty parameter.</dd>
<dt>standardize</dt>
<dd>Logical. If <code>TRUE</code>, x is standardized using the <code>weights</code>.</dd></dl>

Arguments

Finding Ridge Regression Solutions — fastridge

<dl>

<dt>x</dt>
<dd>Regressor matrix.</dd>


<dt>y</dt>
<dd>Dependent variable (a numeric vector).</dd>


<dt>weights</dt>
<dd>Vector of weights.</dd>


<dt>lambda</dt>
<dd>Penalty parameter.</dd>


<dt>standardize</dt>
<dd>Logical. If <code>TRUE</code>, x is standardized using the <code>weights</code>.</dd>

</dl>

fastridge: Finding Ridge Regression Solutions

Description

Usage

Value

Arguments