File List

Here is a list of all files with brief descriptions:

[detail level 1234]

src
likelihoods
Gamma_likelihood.cpp	Fully optimized implementation avoiding all BLAS calls
Gamma_likelihood.hpp	LogLikelihood computation for clustering with cohesion a
Natarajan_likelihood.cpp	Fully optimized implementation avoiding all BLAS calls
Natarajan_likelihood.hpp	LogLikelihood computation for clustering with cohesion and repulsion
Natarajan_likelihood_summaryStats.cpp
Natarajan_likelihood_summaryStats.hpp	LogLikelihood computation for clustering with cohesion and repulsion
Null_likelihood.hpp	LogLikelihood equal to 1 to ignore data contribution and focus on prior
processes
caches
binary_cache.cpp	Implementation of BinaryCache
binary_cache.hpp	Cache for spatial model with binary covariates
continuos_cache.cpp	Implementation of ContinuosCache
continuos_cache.hpp	Cache for spatial model with continuous covariates
spatial_cache.cpp	Implementation of SpatialCache
spatial_cache.hpp	Cache for spatial model with spatial covariates
module
binary_covariate_module.cpp	Implementation of BinaryCovariatesModule
binary_covariate_module.hpp	Covariate-related computations for clustering processes
binary_covariate_module_cache.cpp	Implementation of BinaryCovariatesModuleCache
binary_covariate_module_cache.hpp	Covariate-related computations for clustering processes with cache
categorical_covariate_module.cpp	Implementation of CategoricalCovariatesModule
categorical_covariate_module.hpp	Covariate-related computations for clustering processes
continuos_covariate_module.cpp	Implementation of ContinuosCovariatesModule
continuos_covariate_module.hpp	Covariate-related computations for clustering processes
continuos_covariate_module_cache.cpp	Implementation of ContinuosCovariatesModuleCache
continuos_covariate_module_cache.hpp	Covariate-related computations for clustering processes
spatial_module.cpp	Implementation of SpatialModule
spatial_module.hpp	Spatial helper methods for clustering processes
spatial_module_cache.cpp	Implementation of SpatialModuleCache
spatial_module_cache.hpp	Spatial helper methods for clustering processes (WIP)
DP.cpp	Implementation of Dirichlet Process for Bayesian nonparametric clustering
DP.hpp	Dirichlet Process implementation for Bayesian nonparametric clustering
DPx.cpp	Implementation of Dirichlet Process with module-based similarity terms
DPx.hpp	Dirichlet Process with covariates and modules for Bayesian nonparametric clustering
NGGP.cpp	Implementation of Normalized Generalized Gamma Process
NGGP.hpp	Normalized Generalized Gamma Process (NGGP) implementation for Bayesian nonparametric clustering
NGGPx.cpp	Implementation of NGGP with module-based similarity terms
NGGPx.hpp	Normalized Generalized Gamma Process with module-based covariates
samplers
U_sampler
MALA.cpp	Implementation of the Metropolis-Adjusted Langevin Algorithm (MALA) for sampling the latent variable U
MALA.hpp	Metropolis-Adjusted Langevin Algorithm (MALA) sampler for the latent variable U
RWMH.cpp	Implementation of Random Walk Metropolis-Hastings sampler methods
RWMH.hpp	Random Walk Metropolis-Hastings sampler for the latent variable U
U_sampler.cpp	Implementation of U_sampler class methods
U_sampler.hpp	Base class for sampling the latent variable U in NGGP mixture models
neal.cpp	Implementation of Neal's Algorithm 3 for collapsed Gibbs sampling
neal.hpp	Neal's Algorithm 3 implementation for collapsed Gibbs sampling
neal_ZDNAM.cpp	Implementation of ZDNAM (Zero-self Downward Nested Antithetic Modification)
neal_ZDNAM.hpp	Neal's Algorithm 3 with ZDNAM (Zero-self Downward Nested Antithetic Modification)
splitmerge.cpp	Implementation of Split-Merge MCMC sampler
splitmerge.hpp	Split-Merge MCMC sampler implementation for Bayesian nonparametric models
splitmerge_LSS.cpp	Implementation of Locality Sensitive Sampling (LSS) Split-Merge sampler
splitmerge_LSS.hpp	Locality Sensitive Sampling (LSS) Split-Merge sampler implementation
splitmerge_LSS_SDDS.cpp	Implementation of Locality Sensitive Sampling (LSS) with SDDS Split-Merge sampler
splitmerge_LSS_SDDS.hpp	Locality Sensitive Sampling (LSS) with SDDS Split-Merge sampler implementation
splitmerge_SAMS.cpp	Implementation of Sequential Allocation Merge-Split (SAMS) sampler
splitmerge_SAMS.hpp	Sequential Allocation Merge-Split (SAMS) sampler implementation
utils
ClusterInfo.hpp	Abstract base class for managing cluster information and caches
Data.cpp	Implementation of the Data class
Data.hpp	Data structure for managing point distances and cluster allocations
Datax.cpp	Implementation of Datax class
Datax.hpp	Extended data structure integrating cluster information or caching mechanisms
Likelihood.hpp	Abstract base class for likelihood computation in clustering models
Module.hpp	Base class for modules used in processes
Params.hpp	Parameter management for Bayesian nonparametric MCMC models
Process.hpp	Abstract interface for Bayesian nonparametric processes
Sampler.hpp	Abstract base class for MCMC sampling algorithms
bindings.cpp	R language bindings for Bayesian nonparametric clustering models