kl.process: Create a Process via Karhunen-Loeve Representation

In synfd: Synthesize Dense or Sparse Functional Data/Snippets

Description

Create a Process via Karhunen-Loeve Representation

Usage

kl.process(
  domain = c(0, 1),
  eigen.values = 1/(2^(1:25)),
  eigen.functions = c("FOURIER", "COS", "SIN", "LEGENDRE"),
  distribution = c("GAUSSIAN", "LAPLACE", "EXPONENTIAL", "GAMMA"),
  corr = NULL
)

Arguments

domain	domain of the process.
eigen.values	vector of eigenvalues in the K-L expansion.
eigen.functions	string that specifies the eigenfunctions in the K-L expansion.
distribution	string specifying the distribution of FPC scores.
corr	correlation matrix optionally specifying correlation among the random coefficients; default: NULL.

Value

a function hanlde in the form of X(tObs,n) which generates n independent trajectories observed at tObs.

Examples

X <- kl.process()
X(regular.grid(50),25)

synfd documentation built on July 1, 2020, 6:04 p.m.