MakeGPFunctionalData {fdapace}

Create a Dense Functional Data sample for a Gaussian process

Description

For a Gaussian process, create a dense functional data sample of size n over a [0,1] support.

Usage

MakeGPFunctionalData(
  n,
  M = 100,
  mu = rep(0, M),
  K = 2,
  lambda = rep(1, K),
  sigma = 0,
  basisType = "cos"
)

Arguments

n

number of samples to generate

M

number of equidistant readings per sample (default: 100)

mu

vector of size M specifying the mean (default: rep(0,M))

K

scalar specifying the number of basis to be used (default: 2)

lambda

vector of size K specifying the variance of each components (default: rep(1,K))

sigma

The standard deviation of the Gaussian noise added to each observation points.

basisType

string specifying the basis type used; possible options are: 'sin', 'cos' and 'fourier' (default: 'cos') (See code of 'CreateBasis' for implementation details.)

Value

A list containing the following fields:

Y

A vector of noiseless observations.

Yn

A vector of noisy observations if sigma > 0.