Index
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G
 generateTable, Node
 generateTables, NetworkModel
 getAIC, Domain
 getAlpha, Node
 getApproximationConstant, Domain
 getAttribute
 getBelief, Node
 getBeta, Node
 getBIC, Domain
 getCaseCount, Domain
 getCaseState, Node
 getCaseValue, Node
 getCategory, Node
 getCGSize, Table
 getChildren, Node
 getClassByName, ClassCollection
 getClassCollection, Class
 getCliques, JunctionTree
 getColumnName, DataSet
 getConfiguration, TableCache
 getConflict
 getCovariance, Table
 getCSS, BasicWidget
 getData
 getDataItem
 getDBNWindowOffset, Domain
 getDConnectedNodes, Domain
 getDistribution, Node
 getDomNode, BasicWidget
 getDSeparatedNodes, Domain
 getEdgeConstraint, Node
 getEliminationOrder, Domain
 getEnteredFinding, Node
 getEnteredValue, Node
 getEntropy, Node
 getExpectedUtility
 getExperienceTable, Node
 getExplanation, Domain
 getExplanationScore, Domain
 getExpression, Model
 getFadingTable, Node
 getGamma, Node
 getHAPI
 getHome, Node
 getHomeClass, Node
 getHomeDomain, Node
 getIndex, TableCache
 getInputs, Class
 getInstance, Node
 getInstances, Class
 getJunctionTree
 getJunctionTrees, Domain
 getKind, Node
 getLabel, Node
 getLogLikelihood, Domain
 getLogLikelihoodTolerance, Domain
 getLogNormalizationConstant, Domain
 getMAPConfiguration, Domain
 getMarginal, Domain
 getMaster, Node
 getMaxNumberOfEMIterations, Domain
 getMaxNumberOfSeparators, Domain
 getMean
 getMembers
 getModel, Node
 getMutualInformation, Node
 getName
 getNeighbors, Clique
 getNewBatch, HAPI
 getNewClass, ClassCollection
 getNewClassCollection, HAPI
 getNewDataSet, HAPI
 getNewDomain, HAPI
 getNewInstanceNode, Class
 getNewModel, Domain
 getNewNode, NetworkModel
 getNewRemoteScriptObject, HuginRPC
 getNodeByName, NetworkModel
 getNodes
 getNormalDeviate, Domain
 getNormalizationConstant, Domain
 getNumberOfCases, Domain
 getNumberOfColumns, DataSet
 getNumberOfExplanations, Domain
 getNumberOfMAPConfigurations, Domain
 getNumberOfRows, DataSet
 getNumberOfSamplesPerInterval, Model
 getNumberOfStates, Node
 getOutputs, Class
 getParents, Node
 getPositionX, Node
 getPositionY, Node
 getPredictedBelief, Node
 getPredictedMean, Node
 getPredictedValue, Node
 getPredictedVariance, Node
 getProbabilityOfMAPConfiguration, Domain
 getPropagatedFinding, Node
 getPropagatedValue, Node
 getRequisiteAncestors, Node
 getRequisiteParents, Node
 getRoot, JunctionTree
 getSampledState, Node
 getSampledUtility, Node
 getSampledValue, Node
 getSelectedIndex, SelectOption
 getSelectedState, Node
 getSensitivityConstants, Node
 getSensitivityConstantsByOutput, Node
 getSensitivitySet, Domain
 getSignificanceLevel, Domain
 getSize
 getSource, Node
 getStateIndex, Node
 getStateIndexFromLabel, Node
 getStateLabel, Node
 getStateValue, Node
 getSubtype, Node
 getTable, Node
 getTemporalClone, Node
 getTemporalMaster, Node
 getText, TextInput
 getTotalCGSize, JunctionTree
 getTotalSize, JunctionTree
 getUniformDeviate, Domain
 getValue, Node
 getVariance
 Globals
this.generateTable = function generateTable()
Generates the table of this discrete Node from its Model (a missing Model will trigger an error).
this.generateTables = function generateTables()
Generates the conditional probability tables for all nodes of this NetworkModel.
this.getAIC = function getAIC()
Computes the AIC score (Akaike’s Information Criterion) of the case data.
this.getAlpha = function getAlpha(i)
Returns the alpha component of the CG distribution of this continuous chance node given the discrete parent configuration corresponding to i.
this.getApproximationConstant = function getApproximationConstant()
Returns the approximation constant.
this.getAttribute = function getAttribute(key)
Returns an attribute value.
this.getAttribute = function getAttribute(key)
Returns an attribute value.
this.getBelief = function getBelief(state)
Gets the belief for the specified state of this Node.
this.getBeta = function getBeta(parent,
i)
Returns the beta component of the CG distribution of this continuous chance node given a continuous parent and the discrete parent configuration corresponding to i.
this.getBIC = function getBIC()
Computes the BIC score (Bayesian Information Criterion) of the case data.
this.getCaseCount = function getCaseCount(caseindex)
Returns case count for a case.
this.getCaseState = function getCaseState(c)
Returns the state of this discrete node for case c.
this.getCaseValue = function getCaseValue(caseindex)
Returns the value set for this continuous chance node in case caseindex.
this.getCategory = function getCategory()
Returns the category of this Node.
this.getCGSize = function getCGSize()
Returns the CG size of this Table.
this.getChildren = function getChildren()
Get an array of child Nodes for this Node.
this.getClassByName = function getClassByName(name)
Returns a Class by name.
this.getClassCollection = function getClassCollection()
Get the ClassCollection to which this Class belongs.
this.getCliques = function getCliques()
Get the list of Cliques in this JunctionTree.
this.getColumnName = function getColumnName(column)
Returns the name of the specified column of this DataSet.
this.getConfiguration = function(index,
configuration)
Computes the state configuration corresponding to a given table index.
this.getConflict = function getConflict()
Returns the conflict value.
this.getConflict = function getConflict()
Get the conflict measure of the data inserted in this JunctionTree.
this.getCovariance = function getCovariance(index,
node1,
node2)
Get the covariance of a pair of continuous chance Nodes given a configuration of the discrete chance Nodes of this Table.
owner.getCSS = _deprecated_deprecate(
    owner,
   function getCSS() { return _domNode.style; },
    "BasicWidget.getCSS() - instead use BasicWidget.getDomNode().style"
); _defineconstant_addConstant(this, "toJSON", function() {_error_throwError("cannot serialize hugin widget instance");}); } function CustomWidget(owner)
Easy access to the CSS style property of the corresponding DOM element for this widget.
this.getData = function getData(startIndex,
count)
Gets a region of the discrete data of this Table.
this.getData = function(startIndex,
count)
Gets a region of the discrete data of this TableCache.
this.getDataItem = function getDataItem(row,
column)
Returns the data item at the specified location of this DataSet.
this.getDataItem = function getDataItem(index)
Get the data item at position index of the discrete data of this Table.
this.getDataItem = function(index)
Get the data item at position index of the discrete data of this TableCache.
this.getDBNWindowOffset = function getDBNWindowOffset()
Returns the total number of time steps that the time window of this DBN runtime domain has been moved.
this.getDConnectedNodes = function getDConnectedNodes(source,
hard,
soft)
Performs a d-separation test and returns a list of d-connected nodes.
this.getDistribution = function getDistribution()
Returns the distribution for this continuous node.
owner.getDomNode = function getDomNode()
Get the DOM element corresponding to this widget.
this.getDSeparatedNodes = function getDSeparatedNodes(source,
hard,
soft)
Performs a d-separation test and returns a list of d-separated nodes.
this.getEdgeConstraint = function getEdgeConstraint(node)
Returns the constraint between this and Node.
this.getEliminationOrder = function getEliminationOrder()
Returns the triangulation order.
this.getEnteredFinding = function getEnteredFinding(state)
Returns the entered finding for the specified state of this node.
this.getEnteredValue = function getEnteredValue()
Gets the evidence (value) entered for this continuous chance node.
this.getEntropy = function getEntropy()
Computes the entropy of this node.
this.getExpectedUtility = function getExpectedUtility()
Gets the total expected utility associated with this Domain.
this.getExpectedUtility = function getExpectedUtility(state)
Gets the expected utility associated with this utility node or specified action of this discrete node.
this.getExperienceTable = function getExperienceTable()
Returns the experience table of this continuous or discrete chance node.
this.getExplanation = function getExplanation(index)
Returns the evidence subset associated with the explanation of rank index computed by the most recent call to Node.computeExplanationData.
this.getExplanationScore = function getExplanationScore(index)
Returns the score of the specified explanation.
this.getExpression = function getExpression(index)
Returns the expression (as a string) associated with a specific configuration of the NodeResources of this ModelResource.
this.getFadingTable = function getFadingTable()
Returns the fading table of this discrete chance node.
this.getGamma = function getGamma(i)
Returns the gamma component of the CG distribution of this continuous chance node given the discrete parent configuration corresponding to i.
this.getHAPI = function getHAPI()
Get the HAPI object that owns this Batch
this.getHAPI = function getHAPI()
Get the HAPI object that owns this ClassCollection
this.getHAPI = function getHAPI()
Get the HAPI object that owns this Clique
this.getHAPI = function getHAPI()
Get the HAPI object that owns this DataSet
this.getHAPI = function getHAPI()
Get the HAPI object that owns this JunctionTree
this.getHAPI = function getHAPI()
Get the HAPI object that owns this Model
this.getHAPI = function getHAPI()
Get the HAPI object that owns this NetworkModel
this.getHAPI = function getHAPI()
Get the HAPI object that owns this Node
this.getHAPI = function getHAPI()
Get the HAPI object that owns this Table
this.getHome = function getHome()
Returns the NetworkModel containing this Node.
this.getHomeClass = function getHomeClass()
Returns the Class containing this Node.
this.getHomeDomain = function getHomeDomain()
Returns the Domain containing this Node.
this.getIndex = function(configuration)
Computes the table index corresponding to a given state configuration.
this.getInputs = function getInputs()
Get all input Nodes defined for this Class.
this.getInstance = function getInstance()
Returns the instance Node containing this (cloned) output node.
this.getInstances = function getInstances()
Get all instance Nodes that are instances of this Class.
this.getJunctionTree = function getJunctionTree()
Get the JunctionTree to which this Clique belongs.
this.getJunctionTree = function getJunctionTree()
Returns the JunctionTree to which this Node belongs.
this.getJunctionTrees = function getJunctionTrees()
Gets all JunctionTrees of this Domain.
this.getKind = function getKind()
Returns the kind of this Node.
this.getLabel = function getLabel()
Returns the label of this Node.
this.getLogLikelihood = function getLogLikelihood()
Computes the log-likelihood of the case data.
this.getLogLikelihoodTolerance = function getLogLikelihoodTolerance()
Returns the log-likelihood tolerance for this Domain.
this.getLogNormalizationConstant = function getLogNormalizationConstant()
Returns the log of the normalization constant.
this.getMAPConfiguration = function getMAPConfiguration(index)
Returns a MAP configuration.
this.getMarginal = function getMarginal(nodes)
Computes the marginal distribution for the Nodes provided as argument with respect to the (imaginary) joint potential, determined by the current potentials on the JunctionTrees of this Domain.
this.getMaster = function getMaster()
Returns the “master” of this (cloned) output Node of an instance node (i.e., the node cloned to get this output node).
this.getMaxNumberOfEMIterations = function getMaxNumberOfEMIterations()
Returns the maximum number of iterations allowed for the EM algorithm.
this.getMaxNumberOfSeparators = function getMaxNumberOfSeparators()
Returns the maximum number of separators allowed when using the HAPI.H_TM_TOTAL_WEIGHT triangulation method.
this.getMean = function getMean()
Returns the mean of the marginal distribution of this continuous chance node.
this.getMean = function getMean(index,
node)
Get the mean of a continuous chance Node given a configuration of the discrete chance Nodes of this Table.
this.getMembers = function getMembers()
Get all Classes of this ClassCollection.
this.getMembers = function getMembers()
Get the list of Nodes that are members of this Clique.
this.getModel = function getModel()
Gets the Model for this Node.
this.getMutualInformation = function getMutualInformation(node)
Computes the mutual information between this discrete Node and the specified discrete Node.
this.getName = function getName()
Returns the name of this Class.
this.getName = function getName()
Returns the name of this Node.
this.getNeighbors = function getNeighbors()
Get a list of Cliques that are neighbors of this Clique.
this.getNewBatch = function getNewBatch()
Constructs a new Batch object.
this.getNewClass = function getNewClass(name)
Creates a new Class.
this.getNewClassCollection = function getNewClassCollection()
Construct an empty classcollection.
this.getNewDataSet = function getNewDataSet()
Construct an empty DataSet.
this.getNewDomain = function getNewDomain()
Constructs a new empty Domain.
this.getNewInstanceNode = function getNewInstanceNode(instanceOf)
Creates a new instance Node.
this.getNewModel = function getNewModel(belongsTo,
modelNodes)
Constructs a Model over a Node given a list of Nodes.
this.getNewNode = function getNewNode(category,
kind,
subtype)
Creates a new Node.
this.getNewRemoteScriptObject = function getNewRemoteScriptObject(
    scriptUrl,
   constructorName //,
    arg0,
    arg1,
    ...,
    argN
)
Remotely load a JavaScript file, invoke a JavaScript object constructor, and return a RemoteObject reference to the remotely constructed object.
this.getNodeByName = function getNodeByName(name)
Returns a Node by name.
this.getNodes = function getNodes()
Get all Nodes in this Model.
this.getNodes = function getNodes()
Get all Nodes in this NetworkModel.
this.getNodes = function getNodes()
Get all Nodes associated with this Table.
this.getNodes = function()
Get all Nodes associated with underlying Table.
this.getNormalDeviate = function getNormalDeviate(mean,
variance)
Use the pseudo-random number generator for this Domain to sample a real number from a normal (aka Gaussian) distribution.
this.getNormalizationConstant = function getNormalizationConstant()
Retrieves the normalization constant for the most recent propagation.
this.getNumberOfCases = function getNumberOfCases()
Returns the number of data cases.
this.getNumberOfColumns = function getNumberOfColumns()
Returns the number of columns in this DataSet.
this.getNumberOfExplanations = function getNumberOfExplanations()
Returns the number of explanations.
this.getNumberOfMAPConfigurations = function getNumberOfMAPConfigurations()
Returns the number of MAP configurations.
this.getNumberOfRows = function getNumberOfRows()
Returns the number of rows in this DataSet.
this.getNumberOfSamplesPerInterval = function getNumberOfSamplesPerInterval()
Gets the number of values per interval used when generating the conditional probability table for a node with interval parents.
this.getNumberOfStates = function getNumberOfStates()
Get the number of states of this discrete node.
this.getOutputs = function getOutputs()
Get all output Nodes defined for this Class.
this.getParents = function getParents()
Get an array of parent Nodes for this Node.
this.getPositionX = function getPositionX()
Returns the position of this Node on the X-axis.
this.getPositionY = function getPositionY()
Returns the position of this Node on the Y-axis.
this.getPredictedBelief = function getPredictedBelief(state,
time)
Returns the predicted belief for the specified state of this discrete Node at the specified time point.
this.getPredictedMean = function getPredictedMean(time)
Returns the predicted mean of the marginal distribution of this continuous chance node at the specified time point.
this.getPredictedValue = function getPredictedValue(time)
Gets the predicted value of this FunctionNode at the specified time point.
this.getPredictedVariance = function getPredictedVariance(time)
Returns the predicted variance of the marginal distribution of this continuous chance node at the specified time point.
this.getProbabilityOfMAPConfiguration = function getProbabilityOfMAPConfiguration(
   index
)
Returns the probability of a MAP configuration.
this.getPropagatedFinding = function getPropagatedFinding(state)
Returns the propagated finding.
this.getPropagatedValue = function getPropagatedValue()
Retrieves the value that has been propagated for this continuous chance Node.
this.getRequisiteAncestors = function getRequisiteAncestors()
Get an array of Nodes containing the requisite ancestors of this decision Node.
this.getRequisiteParents = function getRequisiteParents()
Get an array of Nodes containing the requisite parents of this decision Node.
this.getRoot = function getRoot()
Get the root Clique of this JunctionTree.
this.getSampledState = function getSampledState()
Returns the state index of this discrete node for the configuration generated by the most recent call to Domain.simulate.
this.getSampledUtility = function getSampledUtility()
Returns the sampled utility associated with this utility node.
this.getSampledValue = function getSampledValue()
Returns the value of this function or continuous chance Node for the configuration generated by the most recent call to Domain.simulate.
this.getSelectedIndex = function getSelectedIndex()
Gets the index of the currently selected option
this.getSelectedState = function getSelectedState()
Gets (the index of) the selected state of this node.
this.getSensitivityConstants = function getSensitivityConstants(input)
Returns the four constants of the specified sensitivity function.
this.getSensitivityConstantsByOutput = function getSensitivityConstantsByOutput(
   input,
   output
)
Returns the four constants of the specified sensitivity function.
this.getSensitivitySet = function getSensitivitySet()
Returns the sensitivity set computed by the most recent call to Domain.computeSensitivityData.
this.getSignificanceLevel = function getSignificanceLevel()
Returns the significance level of the dependency tests performed during structure learning using the PC-algorithm.
this.getSize = function getSize()
Returns the number of configurations of the Node of this Model.
this.getSize = function getSize()
Get the size of this Table.
this.getSize = function()
Get the size of the underlying Table.
this.getSource = function getSource()
Get an array of Nodes of Class nodes that identifies this Domain node.
this.getStateIndex = function getStateIndex(value)
Get the index of the state matching the specified value.
this.getStateIndexFromLabel = function getStateIndexFromLabel(label)
Returns the index of the state matching the specified label.
this.getStateLabel = function getStateLabel(state)
Gets the label of the specified state.
this.getStateValue = function getStateValue(state)
Gets the value associated with a particular state of this numbered node or the low value of the interval associated with a particular state of this interval node.
this.getSubtype = function getSubtype()
Returns the subtype of this Node.
this.getTable = function getTable()
Gets the Table associated with this Node.
this.getTemporalClone = function getTemporalClone()
Get the “temporal clone” of this Node.
this.getTemporalMaster = function getTemporalMaster()
Get the “temporal master” of this Node.
this.getText = function getText()
Get the contents of this TextInput.
this.getTotalCGSize = function getTotalCGSize()
Get the total number of CG table entries for this JunctionTree.
this.getTotalSize = function getTotalSize()
Get the total number of discrete table configurations for this JunctionTree.
this.getUniformDeviate = function getUniformDeviate()
Use the pseudo-random number generator for this Domain to sample a real number from the uniform distribution over the interval [0,1).
this.getValue = function getValue()
Gets the value of this FunctionNode.
this.getVariance = function getVariance()
Returns the variance of the marginal distribution of this continuous chance Node.
this.getVariance = function getVariance(index,
node)
Get the variance of a continuous chance Node given a configuration of the discrete chance Nodes of this Table.
Close