createSimilarityMat

Constructs a similarity matrix of the pairwise coclustering 
rate.

Semi-supervised and unsupervised Bayesian mixture models that
simultaneously infer the cluster/class structure and a batch correction.
Densities available are the multivariate normal and the multivariate t.
The model sampler is implemented in C++. This package is aimed at analysis of
low-dimensional data generated across several batches. See Coleman et al.
(2022) <doi:10.1101/2022.01.14.476352> for details of the model.

Stephen Coleman

batchmix

Semi-Supervised Bayesian Mixture Models Incorporating Batch
Correction

Paul Kirk

Chris Wallace

createSimilarityMat function

<dl><dt>allocations</dt>
<dd>Matrix of sampled partitions. Columns correspond to 
items/samples being clustered, each row is a sampled partition.//'</dd></dl>

Arguments

Create Similarity Matrix — createSimilarityMat

<dl>

<dt>allocations</dt>
<dd>Matrix of sampled partitions. Columns correspond to 
items/samples being clustered, each row is a sampled partition.//'</dd>

</dl>

createSimilarityMat: Create Similarity Matrix

Description

Usage

Value

Arguments