toydata

datasets

Feed longitudinal data into a Bayesian Latent Factor Model to obtain
a low-rank representation. Parameters are estimated using a Hamiltonian
Monte Carlo algorithm with STAN. See G. Weinrott, B. Fontez, N. Hilgert and
S. Holmes, "Bayesian Latent Factor Model for Functional Data Analysis",
Actes des JdS 2016.

Benedicte Fontez

DrBats

Data Representation: Bayesian Approach That's Sparse

Gabrielle Weinrott

Brigitte Charnomordic

Nadine Hilgert

Susan Holmes

Isabelle Sanchez

toydata function

A list with 5 elements :<dl class="dl-horizontal">
 <dt>Y.simul</dt><dd>a list of simulated data with 3 elements</dd>
 <dt>t.simul</dt><dd>a matrix with 5 rows and 150 columns giving the observation times of the original data</dd>
 <dt>X</dt><dd>the original data matrix with 5 rows and 150 columns</dd>
 <dt>proj.pca</dt><dd>a list with 4 elements : results of the function histoProj(X, t, t.range = c(0, 1000), breaks = 8)</dd>
 <dt>wlu</dt><dd>a list with 4 elements : results of the function W.QR(U, lambda) where U and lambda are the results of the PCA of X</dd>
 </dl>

Format

A toy longitudinal data set — toydata

A list with 5 elements :<dl class='dl-horizontal'>
 <dt>Y.simul</dt><dd>a list of simulated data with 3 elements</dd>
 <dt>t.simul</dt><dd>a matrix with 5 rows and 150 columns giving the observation times of the original data</dd>
 <dt>X</dt><dd>the original data matrix with 5 rows and 150 columns</dd>
 <dt>proj.pca</dt><dd>a list with 4 elements : results of the function histoProj(X, t, t.range = c(0, 1000), breaks = 8)</dd>
 <dt>wlu</dt><dd>a list with 4 elements : results of the function W.QR(U, lambda) where U and lambda are the results of the PCA of X</dd>
 </dl>

A toy longitudinal data set

toydata: A toy longitudinal data set

Description

Usage

Arguments

Format