init_pam

The output of the cobiclust function.

a vector of . The length is equal to the number of colums.

nu_j

an integer specifying the number of groups in rows.

an integer specifying the number of groups in columns.

a logical variable indicating whether to use a common dispersion parameter (akg = FALSE) or a dispersion parameter per cocluster (akg = TRUE).

Initialisation of the co-clusters by partitioning around medoids method.

internal

Implementation of a probabilistic method for biclustering
adapted to overdispersed count data. It is a Gamma-Poisson Latent Block Model.
It also implements two selection criteria in order to select the number of
biclusters.

J Aubert

cobiclust

Biclustering via Latent Block Model Adapted to Overdispersed
Count Data

init_pam function

<dl><dt>x</dt>
<dd>The output of the cobiclust function.</dd>
<dt>nu_j</dt>
<dd>a vector of . The length is equal to the number of colums.</dd>
<dt>a</dt>
<dd>an numeric.</dd>
<dt>K</dt>
<dd>an integer specifying the number of groups in rows.</dd>
<dt>G</dt>
<dd>an integer specifying the number of groups in columns.</dd>
<dt>akg</dt>
<dd>a logical variable indicating whether to use a common dispersion parameter (akg = FALSE) or a dispersion parameter per cocluster (akg = TRUE).</dd></dl>

Arguments

Initialisation of the co-clusters by partitioning around medoids method. — init_pam

<dl>

<dt>x</dt>
<dd>The output of the cobiclust function.</dd>


<dt>nu_j</dt>
<dd>a vector of . The length is equal to the number of colums.</dd>


<dt>a</dt>
<dd>an numeric.</dd>


<dt>K</dt>
<dd>an integer specifying the number of groups in rows.</dd>


<dt>G</dt>
<dd>an integer specifying the number of groups in columns.</dd>


<dt>akg</dt>
<dd>a logical variable indicating whether to use a common dispersion parameter (akg = FALSE) or a dispersion parameter per cocluster (akg = TRUE).</dd>

</dl>

init_pam: Initialisation of the co-clusters by partitioning around medoids method.

Description

Usage

Value

Arguments