predict.PLNfit

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

predict.PLNfit function

<dl><dt>object</dt>
<dd>an R6 object with class <code>PLNfit</code></dd>
<dt>newdata</dt>
<dd>A data frame in which to look for variables and offsets with which to predict</dd>
<dt>type</dt>
<dd>The type of prediction required. The default is on the scale of the linear predictors (i.e. log average count)</dd>
<dt>...</dt>
<dd>additional parameters for S3 compatibility. Not used</dd></dl>

Arguments

Predict counts of a new sample — predict.PLNfit

<dl>

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


<dt>newdata</dt>
<dd>A data frame in which to look for variables and offsets with which to predict</dd>


<dt>type</dt>
<dd>The type of prediction required. The default is on the scale of the linear predictors (i.e. log average count)</dd>


<dt>...</dt>
<dd>additional parameters for S3 compatibility. Not used</dd>

</dl>

Predict counts of a new sample

predict.PLNfit: Predict counts of a new sample

Description

Usage

Value

Arguments