datasets

Spatial clustering with hidden markov random field fitted via EM algorithm, details of which can be found in Yi Yang (2021) <doi:10.1101/2021.06.05.447181>. It is not only computationally efficient and scalable to the sample size increment, but also is capable of choosing the smoothness parameter and the number of clusters as well.

Yi Yang

SC.MEB

Spatial Clustering with Hidden Markov Random Field using
Empirical Bayes

Xingjie Shi

Jin Liu

PC function

It is a matrix containing 5 PCs
the variables are listed as following<dl class="dl-horizontal">
 <dt>PC1</dt><dd>The 1th PC</dd>
 <dt>PC2</dt><dd>The 2th PC</dd>
 ...
 <dt>PC5</dt><dd>The 5th PC</dd>
</dl>

Format

simulated PCs — PC

It is a matrix containing 5 PCs
the variables are listed as following<dl class='dl-horizontal'>
 <dt>PC1</dt><dd>The 1th PC</dd>
 <dt>PC2</dt><dd>The 2th PC</dd>
 ...
 <dt>PC5</dt><dd>The 5th PC</dd>
</dl>

PC: simulated PCs

Description

Usage

Arguments

Format

Examples