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Wiener

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


fdapace

Functional Data Analysis and Empirical Dynamics

v0.5.6
BSD_3_clause + file LICENSE
Authors
Cody Carroll [aut, cre] (<https://orcid.org/0000-0003-3525-8653>), Alvaro Gajardo [aut], Yaqing Chen [aut], Xiongtao Dai [aut], Jianing Fan [aut], Pantelis Z. Hadjipantelis [aut], Kyunghee Han [aut], Hao Ji [aut], Shu-Chin Lin [ctb], Paromita Dubey [ctb], Hans-Georg Mueller [cph, ths, aut], Jane-Ling Wang [cph, ths, aut]
Initial release
2021-01-10,

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