get_variance_covariance_matrix_model

Constructs the variance-covariance matrix for a model using its
<code>get_variance_covariance_matrix_signal</code> method. Supports both single
<code>time_series_model</code> objects and composite <code>sum_model</code> objects.

internal

Implements the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) presented in Voirol, L., Xu, H., Zhang, Y., Insolia, L., Molinari, R. and Guerrier, S. (2024) <doi:10.48550/arXiv.2409.05160>.
The GMWMX estimator allows to estimate functional and stochastic parameters of linear models with correlated residuals in presence of missing data.
The 'gmwmx2' package provides functions to load and plot Global Navigation Satellite System (GNSS) data from the Nevada Geodetic Laboratory and functions to estimate linear model model with correlated residuals in presence of missing data.

Lionel Voirol

gmwmx2

Estimate Functional and Stochastic Parameters of Linear Models
with Correlated Residuals and Missing Data

Haotian Xu

Yuming Zhang

Luca Insolia

Roberto Molinari

Stéphane Guerrier

get_variance_covariance_matrix_model function

<dl><dt>model</dt>
<dd>A <code>time_series_model</code> or <code>sum_model</code>.</dd>
<dt>n</dt>
<dd>Length of the signal.</dd>
<dt>theta</dt>
<dd>Optional parameter vector (already in domain space of the parameters).</dd>
<dt>prep</dt>
<dd>Optional output from <code>prepare_optim_layout(model)</code> (unused for now).</dd></dl>

Arguments

Variance-covariance matrix implied by a model — get_variance_covariance_matrix_model

<dl>

<dt>model</dt>
<dd>A <code>time_series_model</code> or <code>sum_model</code>.</dd>


<dt>n</dt>
<dd>Length of the signal.</dd>


<dt>theta</dt>
<dd>Optional parameter vector (already in domain space of the parameters).</dd>


<dt>prep</dt>
<dd>Optional output from <code>prepare_optim_layout(model)</code> (unused for now).</dd>

</dl>

get_variance_covariance_matrix_model: Variance-covariance matrix implied by a model

Description

Usage

Value

Arguments