update_SSst

internal

Dirichlet process mixture of multivariate normal, skew normal or skew t-distributions
modeling oriented towards flow-cytometry data preprocessing applications. Method is
detailed in: Hejblum, Alkhassimn, Gottardo, Caron & Thiebaut (2019) <doi: 10.1214/18-AOAS1209>.

Boris P. Hejblum

NPflow

Bayesian Nonparametrics for Automatic Gating of Flow-Cytometry
Data

Chariff Alkhassim

Francois Caron

update_SSst function

<dl><dt>z</dt>
<dd>data matrix</dd>
<dt>S</dt>
<dd>previous sufficient statistics</dd>
<dt>ltn</dt>
<dd>random effects</dd>
<dt>scale</dt>
<dd></dd>
<dt>df</dt>
<dd>skew t degrees of freedom</dd>
<dt>hyperprior</dt>
<dd>Default is <code>NULL</code></dd></dl>

Arguments

Return updated sufficient statistics S for skew t-distribution
with data matrix z — update_SSst

<dl>

<dt>z</dt>
<dd>data matrix</dd>


<dt>S</dt>
<dd>previous sufficient statistics</dd>


<dt>ltn</dt>
<dd>random effects</dd>


<dt>scale</dt>
<dd></dd>


<dt>df</dt>
<dd>skew t degrees of freedom</dd>


<dt>hyperprior</dt>
<dd>Default is <code>NULL</code></dd>

</dl>

update_SSst: Return updated sufficient statistics S for skew t-distribution with data matrix z

Description

Usage

Arguments