qukg_calculation

s_ik

t_jg

a matrix of observations. Columns correspond to biological samples and rows to microorganisms.

mu_i

nu_j

alpha_c

Calculate E_q(U_ijr) and E_q(log U_ijr) when U_ijr follows a Gamma(a_k,g,a_k,g)

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

qukg_calculation function

<dl><dt>s_ik</dt>
<dd>s_ik.</dd>
<dt>t_jg</dt>
<dd>t_jg.</dd>
<dt>x</dt>
<dd>a matrix of observations. Columns correspond to biological samples and rows to microorganisms.</dd>
<dt>mu_i</dt>
<dd>mu_i.</dd>
<dt>nu_j</dt>
<dd>nu_j.</dd>
<dt>alpha_c</dt>
<dd>alpha_c.</dd>
<dt>a</dt>
<dd>a0.</dd></dl>

Arguments

Calculate E_q(U_ijr) and E_q(log U_ijr) when U_ijr follows a Gamma(a_k,g,a_k,g) — qukg_calculation

<dl>

<dt>s_ik</dt>
<dd>s_ik.</dd>


<dt>t_jg</dt>
<dd>t_jg.</dd>


<dt>x</dt>
<dd>a matrix of observations. Columns correspond to biological samples and rows to microorganisms.</dd>


<dt>mu_i</dt>
<dd>mu_i.</dd>


<dt>nu_j</dt>
<dd>nu_j.</dd>


<dt>alpha_c</dt>
<dd>alpha_c.</dd>


<dt>a</dt>
<dd>a0.</dd>

</dl>

qukg_calculation: Calculate E_q(U_ijr) and E_q(log U_ijr) when U_ijr follows a Gamma(a_k,g,a_k,g)

Description

Usage

Value

Arguments