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

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

## Arguments

- n_total
An `integer`

indicating the length of the simulated non-stationary white noise process.

- title
A `string`

defining the name of the time series data.

- seed
An `integer`

defined for simulation replication purposes.

- ...
Additional parameters.

## Value

A `vector`

containing the non-stationary white noise process.

## Note

This function generates a non-stationary white noise process whose theoretical maximum overlapping allan variance (MOAV) corresponds to the
theoretical MOAV of the stationary white noise process. This example confirms that the 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.

## Examples

```
Xt = gen_nswn(n_total = 1000)
plot(Xt)
Yt = gen_nswn(n_total = 2000, title = "non-stationary
white noise process", seed = 1960)
plot(Yt)
```