covmat_nswn

This function allows us to calculate the theoretical covariance matrix of a non-stationary
white noise process.

Implements the allan variance and allan variance linear regression estimator for latent time series models. More details about the method can be found, for example, in Guerrier, S., Molinari, R., & Stebler, Y. (2016) <doi:10.1109/LSP.2016.2541867>.

St<c3><a9>phane Guerrier

avar

Allan Variance

Stéphane Guerrier

James Balamuta

Gaetan Bakalli

Roberto Molinari

Justin Lee

Ahmed Radi

Haotian Xu

Yuming Zhang

Nathanael Claussen

Lionel Voirol

covmat_nswn function

<dl><dt>sigma2</dt>
<dd>A <code>double</code> value for the variance parameter \(\sigma ^2\).</dd>
<dt>n_total</dt>
<dd>An <code>integer</code> indicating the length of the whole non-stationary white noise
process.</dd></dl>

Arguments

Author

Calculate Theoretical Covariance Matrix of Non-Stationary White Noise Process — covmat_nswn

<dl>

<dt>sigma2</dt>
<dd>A <code>double</code> value for the variance parameter \(\sigma ^2\).</dd>


<dt>n_total</dt>
<dd>An <code>integer</code> indicating the length of the whole non-stationary white noise
process.</dd>

</dl>

Calculate Theoretical Covariance Matrix of Non-Stationary White Noise Process

covmat_nswn: Calculate Theoretical Covariance Matrix of Non-Stationary White Noise Process

Description

Usage

Value

Arguments

Author

Examples