select_fes

A helper function for <code>xvalidate</code> that filters a list of fixed effects and returns the modified
list. Used to split the fixed effects for cross-validation.

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

select_fes function

<dl><dt>fe_list</dt>
<dd>A list of fixed effects.</dd>
<dt>select_obs</dt>
<dd>A vector of selected observations / rows.</dd>
<dt>list</dt>
<dd>Logical. If <code>TRUE</code>, it returns a list. Otherwise, a data frame.</dd></dl>

Arguments

Filtering fixed effect lists — select_fes

<dl>

<dt>fe_list</dt>
<dd>A list of fixed effects.</dd>


<dt>select_obs</dt>
<dd>A vector of selected observations / rows.</dd>


<dt>list</dt>
<dd>Logical. If <code>TRUE</code>, it returns a list. Otherwise, a data frame.</dd>

</dl>

select_fes: Filtering fixed effect lists

Description

Usage

Value

Arguments