apply_sandwich_correction

Applies either observation-level HC sandwich (via [mgcv::vcov.gam()]) or
cluster-robust sandwich (CR1 via [gam_sandwich_cluster()] or CL2 via
[gam_sandwich_cluster_cl2()]) to a fitted pffr model.

internal

Methods for regression for functional
data, including function-on-scalar, scalar-on-function, and
function-on-function regression. Some of the functions are applicable to
image data.

Julia Wrobel

refund

Regression with Functional Data

Jeff Goldsmith

Fabian Scheipl

Lei Huang

Chongzhi Di

Jonathan Gellar

Jaroslaw Harezlak

Bruce Swihart

Luo Xiao

Ciprian Crainiceanu

Yakuan Chen

Sonja Greven

Lan Huo

So Young Park

Ana-Maria Staicu

Erjia Cui

Ruonan Li

Zheyuan Li

apply_sandwich_correction function

<dl><dt>m</dt>
<dd>Fitted model.</dd>
<dt>algorithm</dt>
<dd>Algorithm symbol.</dd>
<dt>type</dt>
<dd>`"cluster"` (default) for CR1 cluster-robust, `"cl2"` for
leverage-adjusted cluster-robust CL2, or `"hc"` for observation-level HC.</dd></dl>

Arguments

Apply sandwich correction to model covariance matrices — apply_sandwich_correction

<dl>

<dt>m</dt>
<dd>Fitted model.</dd>


<dt>algorithm</dt>
<dd>Algorithm symbol.</dd>


<dt>type</dt>
<dd>`"cluster"` (default) for CR1 cluster-robust, `"cl2"` for
leverage-adjusted cluster-robust CL2, or `"hc"` for observation-level HC.</dd>

</dl>

Apply sandwich correction to model covariance matrices

apply_sandwich_correction: Apply sandwich correction to model covariance matrices

Description

Usage

Value

Arguments