gen_random_2d

Samples from tensor product P-spline prior and evaluates on fixed grids.
Returns a matrix scaled to unit SD.

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

gen_random_2d function

<dl><dt>s_grid</dt>
<dd>First dimension evaluation points.</dd>
<dt>t_grid</dt>
<dd>Second dimension evaluation points.</dd>
<dt>k_s</dt>
<dd>Basis dimension for s.</dd>
<dt>k_t</dt>
<dd>Basis dimension for t.</dd>
<dt>wiggliness</dt>
<dd>Controls smoothness.</dd></dl>

Arguments

Generate 2D random surface from tensor P-spline prior — gen_random_2d

<dl>

<dt>s_grid</dt>
<dd>First dimension evaluation points.</dd>


<dt>t_grid</dt>
<dd>Second dimension evaluation points.</dd>


<dt>k_s</dt>
<dd>Basis dimension for s.</dd>


<dt>k_t</dt>
<dd>Basis dimension for t.</dd>


<dt>wiggliness</dt>
<dd>Controls smoothness.</dd>

</dl>

Generate 2D random surface from tensor P-spline prior

gen_random_2d: Generate 2D random surface from tensor P-spline prior

Description

Usage

Value

Arguments