VB_GMM_Init

Initialise the variational parameters and the hyper parameters

Identification of Latent Patient Phenotype from Electronic Health Records (EHR) Data using Variational Bayes Gaussian Mixture Model for Latent Class Analysis and Variational Bayes regression for Biomarker level shifts, both implemented by Coordinate Ascent Variational Inference algorithms. Variational methods are used to enable Bayesian analysis of very large Electronic Health Records data. For VB GMM details see Bishop (2006,ISBN:9780-387-31073-2). For Logistic VB see Jaakkola and Jordan (2000) <doi:10.1023/A:1008932416310>. Please see preprint of JSS-submitted paper <doi:10.48550/arXiv.2512.14272>.

Brian Buckley

VBphenoR

Variational Bayes for Latent Patient Phenotypes in EHR

Adrian O'Hagan

Marie Galligan

VB_GMM_Init function

<dl><dt>X</dt>
<dd>n x p data matrix (or data frame that will be converted to a matrix).</dd>
<dt>k</dt>
<dd>guess for the number of mixture components.</dd>
<dt>n</dt>
<dd>number of rows in X.</dd>
<dt>prior</dt>
<dd>Prior for the GMM parameters.</dd>
<dt>init</dt>
<dd>initialize the clusters c("random", "kmeans", "dbscan")</dd>
<dt>initParams</dt>
<dd>initialization parameters for dbscan. NULL if dbscan not selected for init.</dd></dl>

Arguments

Initialise the variational parameters and the hyper parameters — VB_GMM_Init

<dl>

<dt>X</dt>
<dd>n x p data matrix (or data frame that will be converted to a matrix).</dd>


<dt>k</dt>
<dd>guess for the number of mixture components.</dd>


<dt>n</dt>
<dd>number of rows in X.</dd>


<dt>prior</dt>
<dd>Prior for the GMM parameters.</dd>


<dt>init</dt>
<dd>initialize the clusters c("random", "kmeans", "dbscan")</dd>


<dt>initParams</dt>
<dd>initialization parameters for dbscan. NULL if dbscan not selected for init.</dd>

</dl>

VB_GMM_Init: Initialise the variational parameters and the hyper parameters

Description

Usage

Value

Arguments