print.mvgam

This function takes a fitted <code>mvgam</code> or <code>jsdgam</code> object and prints a quick summary

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 (2022) <doi:10.1111/2041-210X.13974>.

Nicholas J Clark

mvgam

Multivariate (Dynamic) Generalized Additive Models

Sarah Heaps

Scott Pease

Matthijs Hollanders

print.mvgam function

<dl><dt>x</dt>
<dd><code>list</code> object returned from <code>mvgam</code></dd>
<dt>...</dt>
<dd>Ignored</dd></dl>

Arguments

Author

Summary for a fitted mvgam object — print.mvgam

<dl>

<dt>x</dt>
<dd><code>list</code> object returned from <code>mvgam</code></dd>


<dt>...</dt>
<dd>Ignored</dd>

</dl>

print.mvgam: Summary for a fitted mvgam object

Description

Usage

Value

Arguments

Author

Details