highDimensionARI

This function is used to calculate Adjusted Rand Index (ARI) values for high-dimensional data.

 methods 

A Poisson mixture model is implemented to cluster genes from high-
throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is
performed using either the EM or CEM algorithm, and the slope heuristics are
used for model selection (i.e., to choose the number of clusters).

Andrea Rau

HTSCluster

Clustering High-Throughput Transcriptome Sequencing (HTS) Data

highDimensionARI function

<dl> <dt>x</dt>
<dd>Vector of classification labels</dd> <dt>y</dt>
<dd>Vector of classification labels</dd> <dt>splits</dt>
<dd>Number of subsets data should be split into</dd> <dt>verbose</dt>
<dd><code>TRUE</code> if verbose output is desired</dd></dl>

Arguments

Author

Calculate ARI for high-dimensional data via data splits — highDimensionARI

<dl>

 <dt>x</dt>
<dd>Vector of classification labels</dd>

 <dt>y</dt>
<dd>Vector of classification labels</dd>

 <dt>splits</dt>
<dd>Number of subsets data should be split into</dd>

 <dt>verbose</dt>
<dd><code>TRUE</code> if verbose output is desired</dd>

</dl>

highDimensionARI: Calculate ARI for high-dimensional data via data splits

Description

Usage

Value

Arguments

Author

References