Class List

Here are the classes, structs, unions and interfaces with brief descriptions:

[detail level 12]

CBinaryCache	Cache for spatial model with binary covariates
CClusterStats	Structure to hold statistics for each cluster
CBinaryCovariatesModule	Module for binary covariate-related computations within clustering processes
CBinaryCovariatesModuleCache	Module for binary covariate-related computations within clustering processes
CCategoricalCovariatesModule	Module for categorical covariate-related computations within clustering processes
CClusterInfo	Abstract interface for cluster information management
CContinuosCache	Cache for spatial model with continuous covariates
CClusterStats	Structure to hold statistics for each cluster
CContinuosCovariatesModule	Module for covariate-related computations within clustering processes
CClusterStats	Sufficient statistics for covariate likelihood computations
CContinuosCovariatesModuleCache	Module for covariate-related computations within clustering processes
CData	Manages distance matrices and cluster allocations for points
CDatax	Data container with integrated cluster information management
CDP	Dirichlet Process class for Bayesian nonparametric clustering
CDPx	Dirichlet Process with module-based covariates for Bayesian nonparametric clustering
CGamma_likelihood	Computes log-likelihood for clusters based on distance-based cohesion
CLikelihood	Abstract base class for likelihood computation
CMALA	Metropolis-Adjusted Langevin Algorithm (MALA) sampler for the latent variable U
CModule	Abstract base class for modules used in clustering processes. This class defines the interface for modules that compute similarity contributions based on covariates or other factors
CNatarajan_likelihood	Computes log-likelihood for clusters based on distance-based cohesion and repulsion
CNatarajan_likelihood_summaryStats	Computes log-likelihood for clusters based on distance-based cohesion and repulsion using summary statistics for the repulsion term
CNeal3	Implementation of Neal's Algorithm 3 for collapsed Gibbs sampling
CNeal3ZDNAM	Neal's Algorithm 3 with ZDNAM for improved collapsed Gibbs sampling
CNGGP	Normalized Generalized Gamma Process class for Bayesian nonparametric clustering
CNGGPx	NGGP clustering process with module-based covariates
CNull_likelihood	LogLikelihood equal to 1 to ignore data contribution and focus on prior
CParams	Structure containing all parameters needed for the NGGP (Normalized Generalized Gamma Process) and DP (Dirichlet Process) model
CProcess	Abstract base class for Bayesian nonparametric processes
CRWMH	Random Walk Metropolis-Hastings sampler for updating the latent variable U
CSampler	Abstract base class for MCMC sampler implementations
CSpatialCache	Cache for spatial model with spatial covariates
CClusterStats	Structure to hold statistics for each cluster
CSpatialModule	Module providing spatial methods for processes utilizing spatial information
CSpatialModuleCache	Module providing spatial methods for processes utilizing spatial information
CSplitMerge	Split-Merge sampler for Bayesian nonparametric mixture models
CSplitMerge_LSS	Locality Sensitive Sampling (LSS) Split-Merge sampler for Bayesian nonparametric models
CSplitMerge_LSS_SDDS	Locality Sensitive Sampling (LSS) with SDDS Split-Merge sampler
CSplitMerge_SAMS	Sequential Allocation Merge-Split (SAMS) sampler for Bayesian nonparametric models
CU_sampler	Abstract base class for MCMC sampling of the latent variable U