handle_weights

<code>handle_weights</code> cleans potential sample weights or codes them as ones if they are not specified.

internal

Provides tools for cross-validated Lasso and Post-Lasso estimation.
Built on top of the 'glmnet' package by Friedman, Hastie and Tibshirani (2010) <doi:10.18637/jss.v033.i01>,
the main function plasso() extends the standard 'glmnet' output with coefficient paths
for Post-Lasso models, while cv.plasso() performs cross-validation for both Lasso
and Post-Lasso models and different ways to select the penalty parameter lambda as discussed in Knaus (2021) <doi:10.1111/rssa.12623>.

Knaus Michael C.

plasso

Cross-Validated Post-Lasso

Michael C. Knaus

Stefan Glaisner

handle_weights function

<dl><dt>w</dt>
<dd>Vector or n x 1 matrix of weights or null if no weights provided</dd>
<dt>n</dt>
<dd>Number of observations</dd></dl>

Arguments

Sanitizes potential sample weights — handle_weights

<dl>

<dt>w</dt>
<dd>Vector or n x 1 matrix of weights or null if no weights provided</dd>


<dt>n</dt>
<dd>Number of observations</dd>

</dl>

handle_weights: Sanitizes potential sample weights

Description

Usage

Value

Arguments