Bayesian Clustering of Multivariate Data Under the Dirichlet-Process Prior
Bayesian Clustering of Multivariate Data with the Dirichlet-Process Pr...
Bayesian Clustering with the Dirichlet-Process Prior
The Dirichlet Distribution
Dirichlet Process-Based Markov Chain Monte Carlo (MCMC) Sampler for Mi...
The Multivariate Normal Distribution
Writing Simulation Parameters and Data to Files
Plotting Clustered Mean Vectors
PCA Plot for Posterior Allocation Probability Matrix
Plotting Posterior Estimates of Cluster-Specific Random Effects
Plotting Data Simulated Under A Random-Effects Mixture Model
A Relabel Algorithm
Resampling to Estimate Posterior Allocation Probability Matrix
Data Simulation Under the Random-Effects Mixture Model
Processing Posterior Estimates for Clustering Under DIRECT
A Bayesian clustering method for replicated time series or replicated measurements from multiple experimental conditions, e.g., time-course gene expression data. It estimates the number of clusters directly from the data using a Dirichlet-process prior. See Fu, A. Q., Russell, S., Bray, S. and Tavare, S. (2013) Bayesian clustering of replicated time-course gene expression data with weak signals. The Annals of Applied Statistics. 7(3) 1334-1361. <doi:10.1214/13-AOAS650>.