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