dataExampleMGPR

A list containing data simulated from a MGPR model. 
The dataset contains 30 realisations from a trivariate process. Each of the 
three functions is observed on 250 time points on [0,1].

datasets

Functionalities for modelling functional data with
multidimensional inputs, multivariate functional data, and non-separable
and/or non-stationary covariance structure of function-valued processes.
In addition, there are functionalities for functional regression models where
the mean function depends on scalar and/or functional covariates and
the covariance structure depends on functional covariates.
The development version of the package can be found on
<https://github.com/gpfda/GPFDA-dev>.

Evandro Konzen

GPFDA

Gaussian Process for Functional Data Analysis

dataExampleMGPR function

A list with two elements:<dl>
<dt>input</dt>
<dd>List of 3 numeric vectors, each one being the time 
points where the corresponding function is observed.</dd>
 
<dt>response</dt>
<dd>List of 3 matrices containing the observed 250 datapoints. 
Each column is an independent realisation.</dd>
</dl>

Format

A list containing data simulated from a MGPR model. 
The dataset contains 30 realisations from a trivariate process. Each of the 
three functions is observed on 250 time points on [0,1].

Data simulated in the MGPR example — dataExampleMGPR

A list with two elements:<dl>
<dt>input</dt>
<dd>List of 3 numeric vectors, each one being the time 
points where the corresponding function is observed.</dd>
 
<dt>response</dt>
<dd>List of 3 matrices containing the observed 250 datapoints. 
Each column is an independent realisation.</dd>


</dl>

dataExampleMGPR: Data simulated in the MGPR example

Description

Usage

Arguments

Format

Details