compute_linear_effect

Compute effect: x * beta(t) for scalar covariate with varying coefficient.

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

compute_linear_effect function

<dl><dt>x</dt>
<dd>Numeric vector (length n) of scalar covariate values.</dd>
<dt>beta_t</dt>
<dd>Numeric vector (length(yind)) of varying coefficient.</dd>
<dt>yind</dt>
<dd>Numeric vector of y evaluation points (unused, for API consistency).</dd></dl>

Arguments

Compute linear varying coefficient effect — compute_linear_effect

<dl>

<dt>x</dt>
<dd>Numeric vector (length n) of scalar covariate values.</dd>


<dt>beta_t</dt>
<dd>Numeric vector (length(yind)) of varying coefficient.</dd>


<dt>yind</dt>
<dd>Numeric vector of y evaluation points (unused, for API consistency).</dd>

</dl>

Compute linear varying coefficient effect

compute_linear_effect: Compute linear varying coefficient effect

Description

Usage

Value

Arguments