param1

datasets

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

param1 function

a list of param for bliss model<dl>
 <dt>Q</dt>
<dd>the number of functional covariates</dd> <dt>n</dt>
<dd>the sample size</dd> <dt>p</dt>
<dd>the number of observation times</dd> <dt>beta_shapes</dt>
<dd>the shapes of the coefficient functions</dd> <dt>grids_lim</dt>
<dd>the range of the observation times</dd> <dt>grids</dt>
<dd>the grids of the observation times</dd> <dt>K</dt>
<dd>the number of intervals for the coefficient function</dd>
</dl>

Format

A list of param for bliss model — param1

a list of param for bliss model<dl>
 <dt>Q</dt>
<dd>the number of functional covariates</dd>

 <dt>n</dt>
<dd>the sample size</dd>

 <dt>p</dt>
<dd>the number of observation times</dd>

 <dt>beta_shapes</dt>
<dd>the shapes of the coefficient functions</dd>

 <dt>grids_lim</dt>
<dd>the range of the observation times</dd>

 <dt>grids</dt>
<dd>the grids of the observation times</dd>

 <dt>K</dt>
<dd>the number of intervals for the coefficient function</dd>


</dl>

param1: A list of param for bliss model

Description

Usage

Arguments

Format