precision.inla_rspde

Function to get the precision matrix of an <code>inla_rspde</code> object created with the <code>rspde.matern()</code> function.

Functions that compute rational approximations of fractional elliptic stochastic partial differential equations. The package also contains functions for common statistical usage of these approximations. The main references for rSPDE are Bolin, Simas and Xiong (2023) <doi:10.1080/10618600.2023.2231051> for the covariance-based method and Bolin and Kirchner (2020) <doi:10.1080/10618600.2019.1665537> for the operator-based rational approximation. These can be generated by the citation function in R.

David Bolin

rSPDE

Rational Approximations of Fractional Stochastic Partial
Differential Equations

Alexandre Simas

Finn Lindgren

precision.inla_rspde function

<dl><dt>object</dt>
<dd>The <code>inla_rspde</code> object obtained with the <code>rspde.matern()</code> function.</dd>
<dt>theta</dt>
<dd>If null, the starting values for theta will be used. Otherwise, it must be suplied as a vector.
For stationary models, we have <code>theta = c(log(tau), log(kappa), nu)</code>. For nonstationary models, we have
<code>theta = c(theta_1, theta_2, ..., theta_n, nu)</code>.</dd>
<dt>...</dt>
<dd>Currently not used.</dd></dl>

Arguments

Get the precision matrix of inla_rspde objects — precision.inla_rspde

<dl>

<dt>object</dt>
<dd>The <code>inla_rspde</code> object obtained with the <code>rspde.matern()</code> function.</dd>


<dt>theta</dt>
<dd>If null, the starting values for theta will be used. Otherwise, it must be suplied as a vector.
For stationary models, we have <code>theta = c(log(tau), log(kappa), nu)</code>. For nonstationary models, we have
<code>theta = c(theta_1, theta_2, ..., theta_n, nu)</code>.</dd>


<dt>...</dt>
<dd>Currently not used.</dd>

</dl>

precision.inla_rspde: Get the precision matrix of `inla_rspde` objects

Description

Usage

Value

Arguments

See Also