assemble_cluster_sandwich

Given a per-observation score matrix, aggregates by cluster and forms
\(V_{CL} = c \cdot V_p M_{CL} V_p + B_2\) with HC1 correction.

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

assemble_cluster_sandwich function

<dl><dt>scores</dt>
<dd>Per-observation score matrix (n_obs x p).</dd>
<dt>cluster_id</dt>
<dd>Cluster membership vector.</dd>
<dt>Vp</dt>
<dd>Bayesian posterior covariance (p x p).</dd>
<dt>B2</dt>
<dd>Bias correction matrix (p x p, or scalar 0).</dd></dl>

Arguments

Assemble cluster-robust sandwich from score matrix — assemble_cluster_sandwich

<dl>

<dt>scores</dt>
<dd>Per-observation score matrix (n_obs x p).</dd>


<dt>cluster_id</dt>
<dd>Cluster membership vector.</dd>


<dt>Vp</dt>
<dd>Bayesian posterior covariance (p x p).</dd>


<dt>B2</dt>
<dd>Bias correction matrix (p x p, or scalar 0).</dd>

</dl>

Assemble cluster-robust sandwich from score matrix

assemble_cluster_sandwich: Assemble cluster-robust sandwich from score matrix

Description

Usage

Value

Arguments