Package edu.cmu.tetrad.bayes
Class CptInvariantUpdater
java.lang.Object
edu.cmu.tetrad.bayes.CptInvariantUpdater
- All Implemented Interfaces:
BayesUpdater,ManipulatingBayesUpdater,TetradSerializable,Serializable
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.
- Version:
- $Id: $Id
- Author:
- josephramsey
- See Also:
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Constructor Summary
ConstructorsConstructorDescriptionCptInvariantUpdater(BayesIm bayesIm) Constructor for CptInvariantUpdater.CptInvariantUpdater(BayesIm bayesIm, Evidence evidence) Constructs a new updater for the given Bayes net. -
Method Summary
Modifier and TypeMethodDescriptiondouble[]calculatePriorMarginals(int nodeIndex) Calculates the prior marginal probabilities of the given node.double[]calculateUpdatedMarginals(int nodeIndex) Calculates the updated marginal probabilities of the given node, given the evidence.Getter for the fieldbayesIm.Getter for the fieldevidence.doublegetJointMarginal(int[] variables, int[] values) getJointMarginal.Getter for the fieldmanipulatedBayesIm.getManipulatedGraph.doublegetMarginal(int variable, int value) Returns the marginal probability of the given variable taking the given value, given the evidence.Getter for the fieldupdatedBayesIm.booleanisJointMarginalSupported.static CptInvariantUpdaterGenerates a simple exemplar of this class to test serialization.voidsetEvidence(Evidence evidence) Sets new evidence for the updater.toString()Prints out the most recent marginal.
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Constructor Details
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Method Details
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serializableInstance
Generates a simple exemplar of this class to test serialization.- Returns:
- a
CptInvariantUpdaterobject
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getBayesIm
Getter for the field
bayesIm.- Specified by:
getBayesImin interfaceBayesUpdater- Returns:
- a
BayesImobject
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getManipulatedBayesIm
Getter for the field
manipulatedBayesIm.- Specified by:
getManipulatedBayesImin interfaceManipulatingBayesUpdater- Returns:
- a
BayesImobject
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getManipulatedGraph
getManipulatedGraph.
- Specified by:
getManipulatedGraphin interfaceManipulatingBayesUpdater- Returns:
- a
Graphobject
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getUpdatedBayesIm
Getter for the field
updatedBayesIm.- Specified by:
getUpdatedBayesImin interfaceManipulatingBayesUpdater- Returns:
- a
BayesImobject
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getEvidence
Getter for the field
evidence.- Specified by:
getEvidencein interfaceManipulatingBayesUpdater- Returns:
- a
Evidenceobject
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setEvidence
Sets new evidence for the updater. Once this is called, old updating results should not longer be available.Sets new evidence for the updater. Once this is called, old updating results should not longer be available.
- Specified by:
setEvidencein interfaceBayesUpdater- Specified by:
setEvidencein interfaceManipulatingBayesUpdater- Parameters:
evidence- evidence
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getMarginal
public double getMarginal(int variable, int value) Returns the marginal probability of the given variable taking the given value, given the evidence.Returns the updated graph. This is the graph in which all probabilities of variables conditional on their parents have been updated.
- Specified by:
getMarginalin interfaceBayesUpdater- Specified by:
getMarginalin interfaceManipulatingBayesUpdater- Parameters:
variable- variable indexvalue- category index- Returns:
- P(variable = value | evidence), where evidence is getEvidence().
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isJointMarginalSupported
public boolean isJointMarginalSupported()isJointMarginalSupported.
- Specified by:
isJointMarginalSupportedin interfaceBayesUpdater- Returns:
- a boolean
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getJointMarginal
public double getJointMarginal(int[] variables, int[] values) getJointMarginal.
- Specified by:
getJointMarginalin interfaceBayesUpdater- Parameters:
variables- an array of objectsvalues- an array of objects- Returns:
- a double
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calculatePriorMarginals
public double[] calculatePriorMarginals(int nodeIndex) Calculates the prior marginal probabilities of the given node.- Specified by:
calculatePriorMarginalsin interfaceBayesUpdater- Parameters:
nodeIndex- node index- Returns:
- P(node = value), where value is the value of the node in the Bayes net.
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calculateUpdatedMarginals
public double[] calculateUpdatedMarginals(int nodeIndex) Calculates the updated marginal probabilities of the given node, given the evidence.- Specified by:
calculateUpdatedMarginalsin interfaceBayesUpdater- Parameters:
nodeIndex- node index- Returns:
- P(node = value | evidence), where value is the value of the node in the Bayes net.
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toString
Prints out the most recent marginal.
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