plot.mvgam_residcor

Plot residual correlation estimates from Joint Species Distribution
(<code>jsdgam</code>) or dynamic factor (<code>mvgam</code>) models

Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. Users can build nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2023) <doi:10.1111/2041-210X.13974>.

Nicholas J Clark

mvgam

Multivariate (Dynamic) Generalized Additive Models

plot.mvgam_residcor function

<dl><dt>x</dt>
<dd><code>list</code> object of class <code>mvgam_residcor</code> resulting from a
call to <code>residual_cor(..., summary = TRUE)</code></dd>
<dt>cluster</dt>
<dd>Logical. Should the variables be re-arranged within the plot
to group the correlation matrix into clusters of positive and negative correlations?
Defaults to <code>FALSE</code></dd>
<dt>...</dt>
<dd>ignored</dd></dl>

Arguments

Author

Plot residual correlations based on latent factors — plot.mvgam_residcor

<dl>

<dt>x</dt>
<dd><code>list</code> object of class <code>mvgam_residcor</code> resulting from a
call to <code>residual_cor(..., summary = TRUE)</code></dd>


<dt>cluster</dt>
<dd>Logical. Should the variables be re-arranged within the plot
to group the correlation matrix into clusters of positive and negative correlations?
Defaults to <code>FALSE</code></dd>


<dt>...</dt>
<dd>ignored</dd>

</dl>

plot.mvgam_residcor: Plot residual correlations based on latent factors

Description

Usage

Value

Arguments

Author

Details

See Also