center_ff_beta

Centers beta so that weighted sum over s equals 0 for each t:
sum_s w(s) * beta(s, t) = 0 for all t.
This matches pffr's identifiability constraint for ff terms.
Uses Simpson weights to be consistent with pffr's default integration.

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

center_ff_beta function

<dl><dt>beta_st</dt>
<dd>Numeric matrix (n_xind x n_yind) coefficient surface.</dd>
<dt>xind</dt>
<dd>Numeric vector of x evaluation points (for integration weights).</dd></dl>

Arguments

Center beta(s,t) surface for ff identifiability — center_ff_beta

<dl>

<dt>beta_st</dt>
<dd>Numeric matrix (n_xind x n_yind) coefficient surface.</dd>


<dt>xind</dt>
<dd>Numeric vector of x evaluation points (for integration weights).</dd>

</dl>

Center beta(s,t) surface for ff identifiability

center_ff_beta: Center beta(s,t) surface for ff identifiability

Description

Usage

Value

Arguments