Thesis docs
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Here is a list of all files with brief descriptions:
[detail level 123]
  src
  processes
 DP.cppImplementation of Dirichlet Process for Bayesian nonparametric clustering
 DP.hppDirichlet Process implementation for Bayesian nonparametric clustering
 DPW.cppImplementation of Weighted Dirichlet Process with spatial dependencies
 DPW.hppDirichlet Process with spatial weights (DPW) implementation for spatially-aware Bayesian nonparametric clustering
 NGGP.cppImplementation of Normalized Generalized Gamma Process
 NGGP.hppNormalized Generalized Gamma Process (NGGP) implementation for Bayesian nonparametric clustering
 NGGPW.cppImplementation of Weighted Normalized Generalized Gamma Process
 NGGPW.hppNormalized Generalized Gamma Process with spatial weights (NGGPW) implementation for spatially-aware Bayesian nonparametric clustering
  samplers
 neal.cppImplementation of Neal's Algorithm 3 for collapsed Gibbs sampling
 neal.hppNeal's Algorithm 3 implementation for collapsed Gibbs sampling
 splitmerge.cppImplementation of Split-Merge MCMC sampler
 splitmerge.hppSplit-Merge MCMC sampler implementation for Bayesian nonparametric models
 splitmerge_SAMS.cppImplementation of Sequential Allocation Merge-Split (SAMS) sampler
 splitmerge_SAMS.hppSequential Allocation Merge-Split (SAMS) sampler implementation
  utils
 Data.cppImplementation of the Data class
 Data.hppData structure for managing point distances and cluster allocations
 Likelihood.cppImplementation of the Likelihood class for distance-based clustering
 Likelihood.hppLikelihood computation for clustering with cohesion and repulsion
 Params.hppParameter management for Bayesian nonparametric MCMC models
 Process.hppAbstract interface for Bayesian nonparametric processes
 Sampler.hppAbstract base class for MCMC sampling algorithms
 launcher.cppMain launcher file for MCMC simulation with various Bayesian non-parametric processes