standard_error

standard_error.PLNfit

Extracts univariate standard errors for the estimated coefficient of Theta. Standard errors are computed from the (approximate) Fisher information matrix. See <code>fisher.PLNfit()</code> for more details on the approximations.

The Poisson-lognormal model and variants (Chiquet, Mariadassou and Robin,
2021 <doi:10.3389/fevo.2021.588292>) can be used for
a variety of multivariate problems when count data are at play, including
principal component analysis for count data, discriminant analysis, model-based clustering and
network inference. Implements variational algorithms to fit such models accompanied with a set of
functions for visualization and diagnostic.

Julien Chiquet

PLNmodels

Poisson Lognormal Models

Mahendra Mariadassou

Stéphane Robin

Giovanni Poggiato

François Gindraud

standard_error function

<dl><dt>object</dt>
<dd>an R6 object with class PLNfit</dd>
<dt>type</dt>
<dd>Either <code>Wald</code> (default) or <code>Louis</code>. Approximation scheme used to compute the Fisher information matrix</dd></dl>

Arguments

<ul>
<li><code>standard_error(PLNfit)</code>: Component-wise standard errors of Theta in <code>PLNfit</code></li>
</ul>

Methods (by class)

Component-wise standard errors of Theta — standard_error

<dl>

<dt>object</dt>
<dd>an R6 object with class PLNfit</dd>


<dt>type</dt>
<dd>Either <code>Wald</code> (default) or <code>Louis</code>. Approximation scheme used to compute the Fisher information matrix</dd>

</dl>

standard_error: Component-wise standard errors of Theta

Description

Usage

Value

Arguments

Methods (by class)

See Also

Examples