sim_cond_normal

Create a helper function to simulate from the conditional normal distribution of new data given old data

Fit latent variable models with the GEV distribution as the data likelihood and the GEV parameters following latent Gaussian processes. The models in this package are built using the template model builder 'TMB' in R, which has the fast ability to integrate out the latent variables using Laplace approximation. This package allows the users to choose in the fit function which GEV parameter(s) is considered as a spatially varying random effect following a Gaussian process, so the users can fit spatial GEV models with different complexities to their dataset without having to write the models in 'TMB' by themselves. This package also offers methods to sample from both fixed and random effects posteriors as well as the posterior predictive distributions at different spatial locations. Methods for fitting this class of models are described in Chen, Ramezan, and Lysy (2024) <doi:10.48550/arXiv.2110.07051>.

Meixi Chen

SpatialGEV

Fit Spatial Generalized Extreme Value Models

Martin Lysy

Reza Ramezan

sim_cond_normal function

<dl><dt>joint.mean</dt>
<dd>The length <code>n</code> mean vector of the MVN distribution. By default mu1 is the first <code>m</code> elements of <code>joint.mean</code></dd>
<dt>a</dt>
<dd>A vector of length <code>n-m</code>, the values of mu2 to condition on</dd>
<dt>locs_new</dt>
<dd>A matrix containing the coordiantes of new locations</dd>
<dt>locs_obs</dt>
<dd>A matrix containing the coordinates of observed locations</dd>
<dt>kernel</dt>
<dd>A function (kernel function) that returns a matrix containing the similarity between the two arguments.</dd>
<dt>...</dt>
<dd>Hyperparameters to pass to the kernel function.</dd></dl>

Arguments

Create a helper function to simulate from the conditional normal distribution of new data given old data — sim_cond_normal

<dl>

<dt>joint.mean</dt>
<dd>The length <code>n</code> mean vector of the MVN distribution. By default mu1 is the first <code>m</code> elements of <code>joint.mean</code></dd>


<dt>a</dt>
<dd>A vector of length <code>n-m</code>, the values of mu2 to condition on</dd>


<dt>locs_new</dt>
<dd>A matrix containing the coordiantes of new locations</dd>


<dt>locs_obs</dt>
<dd>A matrix containing the coordinates of observed locations</dd>


<dt>kernel</dt>
<dd>A function (kernel function) that returns a matrix containing the similarity between the two arguments.</dd>


<dt>...</dt>
<dd>Hyperparameters to pass to the kernel function.</dd>

</dl>

sim_cond_normal: Create a helper function to simulate from the conditional normal distribution of new data given old data

Description

Usage

Value

Arguments

Details