Package edu.cmu.tetrad.bayes

package edu.cmu.tetrad.bayes

Class	Description
ApproximateUpdater	Calculates updated marginals for a Bayes net by simulating data and calculating likelihood ratios.
BayesBifParser	The BayesBifParser class provides a set of static methods for parsing Bayesian Network Interchange Format (BIF) files.
BayesBifRenderer	Renders Bayes nets and related models in XML.
BayesIm	Interface implemented by Bayes instantiated models.
BayesImProbs	Calculates cell probabilities from conditional BayesIm probabilities on the fly without constructing the entire table.
BayesPm	Implements a discrete Bayes parametric model--that is, a DAG together with a map from the nodes in the graph to a set of discrete variables, specifying the number of categories for each variable and the name of each category for each variable.
BayesProperties	Calculates some scores for Bayes nets as a whole.
BayesProperties.LikelihoodRet	The LikelihoodRet class represents the result of a likelihood ratio test.
BayesUpdater	Interface for a discrete Bayes updating algorithm.
BayesXmlParser	Parses Bayes elements back to objects.
BayesXmlRenderer	Renders Bayes nets and related models in XML.
BdeMetricCache	Provides a method for computing the score of a model, called the BDe metric (Bayesian Dirchlet likelihood equivalence), given a dataset (assumes no missing values) and a Bayes parameterized network (assumes no latent variables).> 0
CellTableProbs	Estimates probabilities from data by constructing the entire cell count table for the data.
CptInvariantMarginalCalculator	Calculates marginals of the form P(V=v') for an updated Bayes net for purposes of the CPT Invariant Updater.
CptInvariantUpdater	Calculates updated probabilities for variables conditional on their parents as well as single-variable updated marginals for a Bayes IM using an algorithm that restricts expensive updating summations only to conditional probabilities of variables with respect to their parents that change from non-updated to updated values.
CptMap	An interface representing a map of probabilities or counts for nodes in a Bayesian network.
CptMapCounts	Represents a conditional probability table (CPT) in a Bayes net.
CptMapProbs	Represents a conditional probability table (CPT) in a Bayes net.
DataSetProbs	Estimates maximum likelihood probabilities directly from data on the fly.
DirichletBayesIm	Stores Dirichlet pseudocounts for the distributions of each variable conditional on particular combinations of its parent values and, together with Bayes Pm and Dag, provides methods to manipulate these tables.
DirichletDataSetProbs	Estimates probabilities directly from data on the fly using maximum likelihood method.
DirichletEstimator	Estimates a DirichletBayesIm from a DirichletBayesIm (the prior) and a data set.
EmBayesEstimator	Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
EmBayesProperties	Calculates some scores for Bayes nets as a whole.
EmBayesProperties.Estimator	Interface for an estimator.
Evidence	Stores information for a variable source about evidence we have for each variable as well as whether each variable has been manipulated.
ExtraCategoryInterpolator	Returns a data set in variables for columns with missing values are augmented with an extra category that represents the missing values, with missing values being reported as belong this category.
FactoredBayesStructuralEM	Implements the procedure Factored-Bayesian-SEM found on page 6 of "The Bayesian Structural EM Algorithm" by Nir Friedman.> 0
GraphTools	A utility class containing graph function from graph theory.
Identifiability	Identifiability, based on RowSummingExactUpdater
IntAveDataSetProbs	Estimates probabilities directly from data on the fly using maximum likelihood method, with the exception that if rows do not exist in the data satisfying a required condition because certain values are unattested, an attempt is made to remove each relevant column in turn, record the estimated probability with column removed from the condition (if it is defined), and then return the average over the estimated probabilities calculated this way.
JunctionTreeAlgorithm	Junction Tree Algorithm.
JunctionTreeUpdater	Jan 21, 2020 11:03:09 AM
ManipulatingBayesUpdater	Interface for a Bayes updating algorithm that's capable of doing manipulation.
Manipulation	Stores information for a variable source about evidence we have for each variable as well as whether each variable has been manipulated.
MlBayesEstimator	Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
MlBayesEstimatorOld	Estimates parameters of the given Bayes net from the given data using maximum likelihood method.
MlBayesIm	Stores a table of probabilities for a Bayes net and, together with BayesPm and Dag, provides methods to manipulate this table.
MlBayesIm.CptMapType	An enumeration representing the different types of CptMap.
MlBayesIm.InitializationMethod	The InitializationMethod enum represents different methods of initializing a class object.
MlBayesImObs	Stores a table of probabilities for a Bayes net and, together with BayesPm and Dag, provides methods to manipulate this table.
ModeInterpolator	Creates a data set in which missing values in each column are filled using the mode of that column.
ModelGenerator	Provides static methods for generating variants of an input graph.
Proposition	Represents propositions over the variables of a particular BayesIm describing an event of a fairly general sort--namely, conjunctions of propositions that particular variables take on values from a particular disjunctive list of categories.
RowSummingExactUpdater	Performs updating operations on a BayesIm by summing over cells in the joint probability table for the BayesIm.
StoredCellProbs	Creates a table of stored cell probabilities for the given list of variables.
StoredCellProbsObs	Creates a table of stored cell probabilities for the given list of variables.
UpdatedBayesIm	Represents a Bayes IM in which all of the conditional probability tables have been updated to take into account evidence.