Package edu.cmu.tetrad.hybridcg

package edu.cmu.tetrad.hybridcg

Class	Description
HybridCgCutpoints	Utilities to populate HybridCgPm cutpoints for discrete children that have continuous parents.
HybridCgCutpoints.Method	Represents the method used to compute and install cutpoints for continuous parents within a hybrid continuous-discrete graphical model.
HybridCgEstimator	Estimator that prepares cutpoints (binning policy) and then runs MLE via HybridCgIm.HybridEstimator.
HybridCgModel	Mixed Continuous/Discrete model with discretization for discrete children that have continuous parents.
HybridCgModel.HybridCgIm	Represents a hybrid causal graph instantiated model (IM) derived from a hybrid causal graph probabilistic model (PM).
HybridCgModel.HybridCgIm.HybridEstimator	The HybridEstimator class estimates Hybrid Causal Graphical Models using Maximum Likelihood Estimation (MLE).
HybridCgModel.HybridCgIm.Sample	Represents a sample containing continuous and discrete data arrays along with a specified number of rows.
HybridCgModel.HybridCgPm	The HybridCgPm class represents a structural model for hybrid Bayesian networks, which may include both discrete and continuous variables.
HybridCgRowShapeTest	This class contains test cases for validating the behavior of row shapes in the Hybrid Conditional Gaussian Parameter Model (HybridCgPm) when the model includes a discrete child node with continuous parent nodes.
HybridCgVars	The `HybridCgVars` class provides utility methods for constructing and managing hybrid continuous and discrete variables.
TestHybridCgModel	Tests for HybridCgModel.