pesel_homogeneous

Derived under assumption that number of variables tends to infinity
while number of observations is limited.

Automatic estimation of number of principal components in PCA
with PEnalized SEmi-integrated Likelihood (PESEL). See Piotr Sobczyk, Malgorzata Bogdan, Julie Josse
"Bayesian dimensionality reduction with PCA using penalized semi-integrated likelihood"
(2017) <doi:10.1080/10618600.2017.1340302>.

Piotr Sobczyk

pesel

Automatic Estimation of Number of Principal Components in PCA

pesel_homogeneous function

<dl><dt>X</dt>
<dd>a matrix containing only continuous variables</dd>
<dt>minK</dt>
<dd>minimal number of principal components fitted</dd>
<dt>maxK</dt>
<dd>maximal number of principal components fitted</dd></dl>

Arguments

PEnalized SEmi-integrated Likelihood for homogeneous singular values and
large number of variables — pesel_homogeneous

<dl>

<dt>X</dt>
<dd>a matrix containing only continuous variables</dd>


<dt>minK</dt>
<dd>minimal number of principal components fitted</dd>


<dt>maxK</dt>
<dd>maximal number of principal components fitted</dd>

</dl>

pesel_homogeneous: PEnalized SEmi-integrated Likelihood for homogeneous singular values and large number of variables

Description

Usage

Value

Arguments