mmNiWpdf

multivariate Normal inverse Wishart probability density function for multiple inputs

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

mmNiWpdf function

<dl><dt>mu</dt>
<dd>data matrix of dimension <code>p x n</code>, <code>p</code> being the dimension of the
data and n the number of data points, where each column is an observed mean vector.</dd>
<dt>Sigma</dt>
<dd>list of length <code>n</code> of observed variance-covariance matrices,
each of dimensions <code>p x p</code>.</dd>
<dt>U_mu0</dt>
<dd>mean vectors matrix of dimension <code>p x K</code>, <code>K</code> being the number of
distributions for which the density probability has to be evaluated</dd>
<dt>U_kappa0</dt>
<dd>vector of length <code>K</code> of scale parameters.</dd>
<dt>U_nu0</dt>
<dd>vector of length <code>K</code> of degree of freedom parameters.</dd>
<dt>U_lambda0</dt>
<dd>list of length <code>K</code> of variance-covariance matrices,
each of dimensions <code>p x p</code>.</dd>
<dt>Log</dt>
<dd>logical flag for returning the log of the probability density
function. Defaults is <code>TRUE</code>.</dd></dl>

Arguments

multivariate Normal inverse Wishart probability density function for multiple inputs — mmNiWpdf

<dl>

<dt>mu</dt>
<dd>data matrix of dimension <code>p x n</code>, <code>p</code> being the dimension of the
data and n the number of data points, where each column is an observed mean vector.</dd>


<dt>Sigma</dt>
<dd>list of length <code>n</code> of observed variance-covariance matrices,
each of dimensions <code>p x p</code>.</dd>


<dt>U_mu0</dt>
<dd>mean vectors matrix of dimension <code>p x K</code>, <code>K</code> being the number of
distributions for which the density probability has to be evaluated</dd>


<dt>U_kappa0</dt>
<dd>vector of length <code>K</code> of scale parameters.</dd>


<dt>U_nu0</dt>
<dd>vector of length <code>K</code> of degree of freedom parameters.</dd>


<dt>U_lambda0</dt>
<dd>list of length <code>K</code> of variance-covariance matrices,
each of dimensions <code>p x p</code>.</dd>


<dt>Log</dt>
<dd>logical flag for returning the log of the probability density
function. Defaults is <code>TRUE</code>.</dd>

</dl>

mmNiWpdf: multivariate Normal inverse Wishart probability density function for multiple inputs

Description

Usage

Value

Arguments