Wiener: Simulate a standard Wiener processes (Brownian motions)

In hadjipantelis/tPACE: Functional Data Analysis and Empirical Dynamics

Simulate a standard Wiener processes (Brownian motions)

Description

Simulate n standard Wiener processes on [0, 1], possibly sparsifying the results.

Usage

Wiener(n = 1, pts = seq(0, 1, length = 50), sparsify = NULL, K = 50)

Arguments

n	Sample size.
pts	A vector of points in [0, 1] specifying the support of the processes.
sparsify	A vector of integers. The number of observations per curve will be uniform distribution on sparsify.
K	The number of components.

Details

The algorithm is based on the Karhunen-Loève expansion of the Wiener process

Value

If sparsify is not specified, a matrix with n rows corresponding to the samples are returned. Otherwise the sparsified sample is returned.

See Also

Sparsify

hadjipantelis/tPACE documentation built on Aug. 16, 2022, 10:45 a.m.