gen_nswn: Generate Non-Stationary White Noise Process

Description Usage Arguments Value Note Author(s) Examples

View source: R/avns.R

Description

This function allows us to generate a non-stationary white noise process.

Usage

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gen_nswn(n_total, title = NULL, seed = 135, ...)

Arguments

n_total

An integer indicating the length of the whole non-stationary white noise process.

title

A string of the time series data name.

seed

An integer set for simulation replication purpose.

...

Additional parameters.

Value

A vector containing the non-stationary white noise process.

Note

This function helps generate a non-stationary process example, non-stationary white noise, whose theoretical maximum overlapping allan variance (MOAV) corresponds to the theoretical MOAV of the stationary white noise process. This example confirms that allan variance is unable to distinguish between a stationary white noise process and a white noise process whose second-order behavior is non-stationary, as pointed out in the paper "A Study of the Allan Variance for Constant-Mean Non-Stationary Processes" by Xu et al. (IEEE Signal Processing Letters, 2017), preprint available: https://arxiv.org/abs/1702.07795.

Author(s)

Yuming Zhang

Examples

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Xt = gen_nswn(n_total = 1000)
plot(Xt)

Yt = gen_nswn(n_total = 2000, title = "non-stationary 
white noise process", seed = 1960)
plot(Yt)

SMAC-Group/simts documentation built on May 23, 2018, 7:32 p.m.