build_Fourier_basis

Define a Fourier basis to simulate functional covariate observations.

A method for the Bayesian functional linear regression model (scalar-on-function),
including two estimators of the coefficient function and an estimator of its support.
A representation of the posterior distribution is also available. Grollemund P-M., Abraham C.,
Baragatti M., Pudlo P. (2019) <doi:10.1214/18-BA1095>.

Paul-Marie Grollemund

bliss

Bayesian Functional Linear Regression with Sparse Step Functions

Isabelle Sanchez

Meili Baragatti

build_Fourier_basis function

<dl><dt>grid</dt>
<dd>a numerical vector.</dd>
<dt>dim</dt>
<dd>a numerical value. It corresponds to <code>dim(basis)/2</code>.</dd>
<dt>per</dt>
<dd>a numerical value which corresponds to the period of the sine and
cosine functions.</dd></dl>

Arguments

build_Fourier_basis — build_Fourier_basis

<dl>

<dt>grid</dt>
<dd>a numerical vector.</dd>


<dt>dim</dt>
<dd>a numerical value. It corresponds to <code>dim(basis)/2</code>.</dd>


<dt>per</dt>
<dd>a numerical value which corresponds to the period of the sine and
cosine functions.</dd>

</dl>

build_Fourier_basis: build_Fourier_basis

Description

Usage

Value

Arguments

Details

Examples