Adapts this DomainResource according to the evidence entered.

For each discrete node of this DomainResource (which must be a runtime domain) such that both the node and its source node have experience tables, the conditional probability and experience tables of both nodes are learned/updated, and the tables of the domain node will be identical to those of its source node.

This function updates (adapts), for all discrete chance nodes of this DomainResource, the experience count (retrieval of experience) and the conditional probability distribution (dissemination of experience) for all parent configurations having a valid experience count.

Adds the specified range of rows of the data set to this DomainResource as cases.

Adds a NodeResource as a new parent of this NodeResource.

Makes this NodeResoruce become an input node of its ClassResource.

Makes this NodeResource become an output node of its ClassResource.

Removes “near-zero” probabilities from the clique probability tables.

Generates a number of sample configurations by invoking DomainResource -> /simulate a number of times and for each iteration recording the results of NodeResource -> /getSampledValue , NodeResource -> /getSampledState or NodeResource -> /getSampledUtility for specified NodeResources.

Returns true if a value has been set for this continuous chance or discrete node in case {caseindex}; otherwise, returns false.

Check if evidence on CG nodes has been propagated.

Returns true if CG evidence has been propagated in this junction tree; otherwise, returns false.

Compiles this DomainResource.

Removes the zero entries from the clique and separator tables of the junction trees in this DomainResource.

Computes predictions for {numberOfTimePoints} time slices beyond the current time window.

Computes Bayes factor data for all (nonempty) subsets of evidence nodes up to the specified maximum size.

Computes “normalized likelihoods” for the specified hypothesis and all (nonempty) subsets of evidence nodes up to the specified maximum size.

Computes the probability of the given interval for the mixture distribution represented by this TableResource.

Computes the constants of the sensitivity functions for the specified output probabilities and all CPT parameters in the network.

Computes the constants of the sensitivity functions for the specified output probability and all CPT/policy parameters in the network.

Creates a DBN runtime DomainResource from this ClassResource.

Creates a flat runtime DomainResource from this ClassResource.

Constructs a temporal clone of this NodeResource.

Deletes this ClassCollectionResource, including all nested HUGIN resources belonging to it (e.g., ClassResources, NodeResources, TableResources etc.)

Deletes this DataSetResource.

Deletes this ModelResource.

Deletes this NetworkModelResource, including all nested HUGIN resources belonging to it (e.g., NodeResources, TableResources etc.)

Deletes this NodeResource.

Deletes this TableResource.

Deletes the specified column from this DataSet.

Deletes the specified row from this DataSet.

Get this ClassCollectionResource in the form of a HKB file.

Get this DataSetResource in the form of a CSV file.

Get this DomainResource in the form of a HKB file.

Enters a case as evidence.

Specifies a finding value for a given state with all other states unaffected.

Enters evidence (observation of the value) for this continuous chance node.

Tests the Equilibrium type.

Tests the Equilibrium type.

Test if the evidence potential, currently registered with this NodeResource, is non-vacuous.

Tests if evidence has been propagated for this DomainResource.

Tests if evidence has been propagated for this JunctionTreeResource.

Returns true if the evidence potential for this NodeResource, incorporated within the current junction tree potentials, is non-vacuous; otherwise, returns false.

Tests for evidence mode.

Tests if the EvidenceMode matches {mode}.

Tests if evidence has been entered since the last propagation.

Tests if evidence has been entered since the last propagation.

Returns true if the entered and the propagated evidence differ; otherwise, returns false.

Finds all configurations of nodes with probability at least {minprobability}.

Generates the table of this discrete node from its model (a missing model will trigger an error).

Generates the conditional probability tables for all nodes of this NetworkModelResource.

Computes the AIC score (Akaike’s Information Criterion) of the case data.

Returns the alpha component of the CG distribution of this continuous chance node given the discrete parent configuration corresponding to {i}.

Returns the approximation constant.

Returns an attribute value.

Returns an attribute value.

Gets the belief for the specified state of this NodeResource.

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}.

Computes the BIC score (Bayesian Information Criterion) of the case data.

Returns case count for a case.

Returns the state of this discrete node for case {c}.

Returns the value set for this continuous chance node in case {caseindex}.

Returns the category of this NodeResource.

Returns the CG size of this TableResource.

Get list of child nodes for this NodeResource.

Returns a ClassResource by name.

Get the ClassCollectionResource to which this ClassResource belongs.

Returns the list of CliqueResources in this JunctionTreeResource.

Returns the name of the specified column of this DataSet.

Returns the conflict value.

Returns the conflict measure of the data inserted in this JunctionTreeResource.

Returns the covariance of a pair of continuous chance NodeResources given a configuration of the discrete chance NodeResources of this TableResource.

Gets a region of the discrete data of this TableResource.

Returns the data item at the specified location of this DataSet.

Get the data item at position {index} of the discrete data of this TableResource.

Returns the total number of time steps that the time window of this DBN runtime domain has been moved.

Performs a d-separation test and returns a list of d-connected nodes.

Returns the distribution for this continuous node.

Performs a d-separation test and returns a list of d-separated nodes.

Returns the constraint between this and node.

Returns the triangulation order.

Returns the entered finding for the specified state of this node.

Returns the evidence (value) entered for this continuous chance node.

Computes the entropy of this node.

Gets the total expected utility associated with this DomainResource.

Gets the expected utility associated with this utility node or specified action of this discrete decision node.

Returns the experience table of this continuous or discrete chance node.

Returns the evidence subset associated with the explanation of rank index computed by the most recent call to NodeResource -> /computeExplanationData.

Returns the score of the specified explanation.

Returns the expression (as a string) associated with a specific configuration of the NodeResources of this ModelResource.

Returns the fading table of this discrete chance node.

Returns the gamma component of the CG distribution of this continuous chance node given the discrete parent configuration corresponding to {i}.

Returns the ClassResource or DomainResource containing this NodeResource.

Returns the ClassResource containing this NodeResource.

Returns the DomainResource containing this NodeResource.

Get all input NodeResources defined for this ClassResource.

Returns the instance NodeResource containing this (cloned) output node.

Get all instance NodeResources that are instances of this ClassResource.

Get the JunctionTreeResource to which this CliqueResource belongs.

Returns the JunctionTreeResource to which this NodeResource belongs.

Gets all JunctionTreeResources of this DomainResource.

Returns the kind of this NodeResource.

Returns the label of this NodeResource.

Computes the log-likelihood of the case data.

Returns the log-likelihood tolerance for this DomainResource.

Returns the log of the normalization constant.

Returns a MAP configuration.

Computes the marginal distribution for the nodes provided as argument with respect to the (imaginary) joint potential, determined by the current potentials on the junction tree(s) of this DomainResource.

Returns the “master” of this (cloned) output NodeResource of an instance node (i.e., the node cloned to get this output node).

Returns the maximum number of iterations allowed for the EM algorithm.

Returns the maximum number of separators allowed when using the total weight triangulation method.

Returns the mean of the marginal distribution of this continuous chance node.

Returns the mean of a continuous chance NodeResource given a configuration of the discrete chance NodeResources of this TableResource.

Get all ClassResources of this ClassCollectionResource.

Get the list of NodeResources that are members of this CliqueResource.

Gets the ModelResource for this NodeResource.

Computes the mutual information between this node and the specified node.

Returns the name of this ClassResource.

Returns the name of this NodeResource.

Returns a list of CliqueResources that are neighbors of this CliqueResource.

Creates a new ClassResource.

Creates a new instance node NodeResource.

Constructs a ModelResource over a NodeResource given a list of NodeResources.

Creates a new NodeResource.

Returns a NodeResource by name.

Returns the list of NodeResources in this ModelResource.

Get all NodeResources in this NetworkModelResource.

Get all NodeResources associated with this TableResource.

Use the pseudo-random number generator for this DomainResource to sample a real number from a normal (aka Gaussian) distribution.

Retrieves the normalization constant for the most recent propagation.

Returns the number of data cases.

Returns the number of columns in this DataSet.

Returns the number of explanations.

Returns the number of MAP configurations.

Returns the number of rows in this DataSet.

Gets the number of values per interval used when generating the conditional probability table for a node with interval parents.

Get the number of states of this discrete node.

Get all output NodeResources defined for this ClassResource.

Get list of parent nodes for this NodeResource.

Returns the position of this NodeResource on the X-axis.

Returns the position of this NodeResource on the Y-axis.

Returns the predicted belief for the specified state of this discrete NodeResource at the specified time point.

Returns the predicted mean of the marginal distribution of this continuous chance node at the specified time point.

Gets the predicted value of this FunctionNode at the specified time point.

Returns the predicted variance of the marginal distribution of this continuous chance node at the specified time point.

Returns the probability of a MAP configuration.

Returns the propagated finding.

Retrieves the value that has been propagated for this continuous chance node.

Returns a white-space separated list of URI references to the requisite ancestors of this decision node.

Returns a white-space separated list of URI references to the requisite parents of this decision node.

Returns the root CliqueResource of this JunctionTreeResource.

Returns the state index of this discrete node for the configuration generated by the most recent call to DomainResource -> /simulate.

Returns the sampled utility associated with this utility node.

Returns the value of this function or continuous chance node for the configuration generated by the most recent call to DomainResource -> /simulate.

Gets (the index of) the selected state of this node.

Returns the four constants of the specified sensitivity function.

Returns the four constants of the specified sensitivity function.

Returns the sensitivity set computed by the most recent call to DomainResource -> /computeSensitivityData.

Returns the significance level of the dependency tests performed during structure learning using the PC-algorithm.

Returns the number of configurations of the NodeResources of this ModelResource.

Get the size of this TableResource.

Get a list of NodeResources of ClassResource nodes that identifies this DomainResource node.

Get the index of the state matching the specified value.

Returns the index of the state matching the specified {label}.

Gets the label of the specified 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.

Returns the subtype of this NodeResource.

Gets the TableResource associated with this NodeResource.

Get the “temporal clone” of this NodeResource.

Get the “temporal master” of this NodeResource.

Returns the total number of CG table entries for this JunctionTreeResource.

Returns the total number of discrete table configurations for this JunctionTreeResource.

Use the pseudo-random number generator for this DomainResource to sample a real number from the uniform distribution over the interval [0,1).

Gets the value of this FunctionNode.

Returns the variance of the marginal distribution of this continuous chance node.

Returns the variance of a continuous chance NodeResource given a configuration of the discrete chance NodeResources of this TableResource.

Returns true if this continuous or discrete chance node has an experience table; returns false otherwise.

Returns true if this discrete chance node has a fading table; returns false otherwise.

Establishes the initial values for all tables of this DomainResource (which must be compiled).

Moves the time window of this DBN back to its initial position, and removes all evidence.

Tests whether this DomainResource is compiled.

Tests whether this DomainResource is compressed.

Tests whether this DomainResource is triangulated.

Tests whether this DomainResource has been triangulated for Boyen-Koller approximate inference.

Touch the ClassCollectionResource to mark it as active in periods where no other functions are being called.

Touch the DataSetResource to mark it as active in periods where no other functions are being called.

Touch the DomainResource to mark it as active in periods where no other functions are being called.

Learns the structure (graph) of the Bayesian network from data using the PC algorithm.

Learns the conditional probability tables from data using the EM algorithm.

Returns true if the evidence potential, currently registered with this NodeResource, is a likelihood; otherwise, returns false.

Returns true if likelihood has been propagated for this DomainResource; otherwise, returns false.

Returns true if likelihoods have been propagated in this JunctionTreeResource; otherwise, returns false.

Returns true if the evidence potential for this NodeResource, incorporated within the current junction tree potentials, is a likelihood; otherwise, returns false.

Construct a classcollection from a HUGIN Knowledge Base retrieved over HTTP.

Construct a domain from a HUGIN Knowledge Base retrieved over HTTP.

Construct a data set from a CSV file retrieved over HTTP.

Construct a domain from a HUGIN Knowledge Base retrieved over HTTP.

Moves the specified column to a new position.

Slides the time window of this DBN delta steps into the future.

Moves the specified row to a new position.

Creates a new case.

Construct an empty classcollection.

Creates a new column in this DataSet.

Construct an empty data set.

Construct an empty domain.

Creates a new row in this DataSet.

Parses a case retrieved from an URL and enters the associated findings into this DomainResource.

Parses the cases retrieved form an URL and enters the cases into this DomainResource.

Parses the file retrieved from an URL and returns a white-space separated list of URI references to NodeResources.

Establishes the specified equilibrium using the evidence mode indicated for incorporation of evidence on all JunctionTrees of this DomainResource.

Propagates evidence in this JunctionTreeResource.

Removes this NodeResource from the set of input nodes of its class.

Removes this NodeResource from the set of output nodes of its class.

Removes the directed link between a parent and this NodeResource.

Reorders the list of NodeResource of this TableResource.

Establishes the initial state of the inference engine, which is sum-equilibrium with no evidence incorporated.

Retracts (all) evidence for all nodes in this DomainResource.

Retracts all findings for this NodeResource.

Reverses the edge between this NodeResource and the specified neighbor.

Experimental JSON batch feature.

Submits this ClassCollectionResource in the form of a HKB file to the service located at a target URL.

Submits this DataSetResource in the form of a CSV file to the service located at a target URL.

Submits this DomainResource in the form of a HKB file to the service located at a target URL.

Submits all evidence entered in this DomainResource to the service located at a target URL.

Submits all cases in this DomainResource to the service located at a target URL.

Creates a copy in memory of the belief and junction tree tables of this DomainResource.

Seeds the pseudo-random number generator for this DomainResource.

Selects the specified state of this NodeResource.

Sets all data items of the discrete data of this TableResource.

Sets the alpha component of the CG distribution of this continuous chance node given the discrete parent configuration corresponding to {i}.

Inserts the key/value pair in the attribute list for this NetworkModelResource.

Sets a value for a particular attribute in the attribute list for this NodeResource.

Sets the beta component of the CG distribution of this continuous chance node given a continuous parent and the discrete parent configuration corresponding to {i}.

Sets case count for a case.

Sets the state of this discrete node to {state} in case {c}.

Sets the value of this continuous chance node to {value} in case {c}.

Sets the name of the specified column of this DataSet.

Sets a region of the discrete data of this TableResource.

Sets (or deletes) the data item at the specified location of this DataSet.

Sets a specific data item of the discrete data of this TableResource.

Sets a constraint between this NodeResource and another NodeResource.

Associates an expression (specified as a string) with a specific configuration of the NodeResources of this ModelResource.

Sets the gamma component of the CG distribution of this continuous chance node given the discrete parent configuration corresponding to {i}.

Sets the label of this NodeResource.

Sets the log-likelihood tolerance for this DomainResource.

Sets the maximum number of iterations allowed for the EM algorithm.

Sets the maximum number of separators allowed when using the total weight triangulation method.

Sets the name of this ClassResource.

Sets the name of this NodeResource.

Sets the number of cases.

Sets the number of values taken within each bounded interval of an interval parent when generating the conditional probability table for a node with interval parents.

Sets the number of states of this NodeResource.

Sets the position of this NodeResource.

Sets the significance level of the dependency tests performed during structure learning using the PC-algorithm.

Sets the label of the specified state.

Sets 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.

Sets the function associated with this function node to a number value.

Generates a sample configuration from the joint distribution represented by this DomainResource.

Replace the given parent node with the new node.

Tests for new node tables.

Returns true if this JunctionTreeResource contains updated tables that have not been propagated; otherwise, returns false.

Triangulates the graph of this DomainResource using the default triangulation method.

Triangulates a DomainResource produced by ClassResource -> /createDBNDomain such that DomainResource -> /moveDBNWindow can be used.

Triangulates a DomainResource produced by ClassResource -> /createDBNDomain such that DomainResource -> /moveDBNWindow can be used.

Triangulates the graph of this DomainResource using the specified triangulation method.

Uncompiles this DomainResource.

Specifies that the value of this continuous chance or discrete node is “unknown” for case {caseindex}.

Updates the policy tables of the domain.