vcov.walsNB

This method always raises an error because the covariance matrix of the
walsNB estimator has not been derived yet.

Implements Weighted-Average Least Squares model averaging
for negative binomial regression models of Huynh (2024) <doi:10.48550/arXiv.2404.11324>,
generalized linear models of De Luca, Magnus, Peracchi (2018)
<doi:10.1016/j.jeconom.2017.12.007> and linear regression models of
Magnus, Powell, Pruefer (2010) <doi:10.1016/j.jeconom.2009.07.004>, see also
Magnus, De Luca (2016) <doi:10.1111/joes.12094>. Weighted-Average Least Squares
for the linear regression model is based on the original 'MATLAB' code by
Magnus and De Luca <https://www.janmagnus.nl/items/WALS.pdf>, see also
Kumar, Magnus (2013) <doi:10.1007/s13571-013-0060-9> and
De Luca, Magnus (2011) <doi:10.1177/1536867X1201100402>.

Kevin Huynh

WALS

Weighted-Average Least Squares Model Averaging

vcov.walsNB function

<dl><dt>object</dt>
<dd>An object of class <code>"walsNB"</code>.</dd>
<dt>...</dt>
<dd>For expansion in the future.</dd></dl>

Arguments

Calculate Variance-Covariance Matrix for a "walsNB" object — vcov.walsNB

<dl>

<dt>object</dt>
<dd>An object of class <code>"walsNB"</code>.</dd>


<dt>...</dt>
<dd>For expansion in the future.</dd>

</dl>

vcov.walsNB: Calculate Variance-Covariance Matrix for a `"walsNB"` object

Description

Usage

Value

Arguments