This function allows to generate a non-stationary bias-instability process.

`gen_bi(sigma2, n_total, n_block, title = NULL, seed = 135, ...)`

## Arguments

- sigma2
A `double`

value for the variance parameter \(\sigma ^2\).

- n_total
An `integer`

indicating the length of the simulated bias-instability process.

- n_block
An `integer`

indicating the length of each block of the bias-instability 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 bias-instability process.

## Note

This function generates a non-stationary bias-instability process
whose theoretical maximum overlapping allan variance (MOAV) is close to the theoretical
MOAV of the best approximation of this process through a stationary AR(1) process over some scales. However, this approximation
is not good enough when considering the logarithmic representation of the allan variance.
Therefore, the exact form of the allan variance of this non-stationary process allows us
to better interpret the signals characterized by bias-instability, as shown in "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_bi(sigma2 = 1, n_total = 1000, n_block = 10)
plot(Xt)
Yt = gen_bi(sigma2 = 0.8, n_total = 800, n_block = 20,
title = "non-stationary bias-instability process")
plot(Yt)
```