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 SummaryConstructorsConstructorDescriptionCptInvariantUpdater(BayesIm bayesIm) Constructor for CptInvariantUpdater.CptInvariantUpdater(BayesIm bayesIm, Evidence evidence) Constructs a new updater for the given Bayes net.
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Method SummaryModifier 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- 
serializableInstanceGenerates a simple exemplar of this class to test serialization.- Returns:
- a CptInvariantUpdaterobject
 
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getBayesImGetter for the field bayesIm.- Specified by:
- getBayesImin interface- BayesUpdater
- Returns:
- a BayesImobject
 
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getManipulatedBayesImGetter for the field manipulatedBayesIm.- Specified by:
- getManipulatedBayesImin interface- ManipulatingBayesUpdater
- Returns:
- a BayesImobject
 
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getManipulatedGraphgetManipulatedGraph. - Specified by:
- getManipulatedGraphin interface- ManipulatingBayesUpdater
- Returns:
- a Graphobject
 
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getUpdatedBayesImGetter for the field updatedBayesIm.- Specified by:
- getUpdatedBayesImin interface- ManipulatingBayesUpdater
- Returns:
- a BayesImobject
 
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getEvidenceGetter for the field evidence.- Specified by:
- getEvidencein interface- ManipulatingBayesUpdater
- Returns:
- a Evidenceobject
 
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setEvidenceSets 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 interface- BayesUpdater
- Specified by:
- setEvidencein interface- ManipulatingBayesUpdater
- Parameters:
- evidence- evidence
 
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getMarginalpublic 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 interface- BayesUpdater
- Specified by:
- getMarginalin interface- ManipulatingBayesUpdater
- Parameters:
- variable- variable index
- value- category index
- Returns:
- P(variable = value | evidence), where evidence is getEvidence().
 
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isJointMarginalSupportedpublic boolean isJointMarginalSupported()isJointMarginalSupported. - Specified by:
- isJointMarginalSupportedin interface- BayesUpdater
- Returns:
- a boolean
 
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getJointMarginalpublic double getJointMarginal(int[] variables, int[] values) getJointMarginal. - Specified by:
- getJointMarginalin interface- BayesUpdater
- Parameters:
- variables- an array of objects
- values- an array of objects
- Returns:
- a double
 
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calculatePriorMarginalspublic double[] calculatePriorMarginals(int nodeIndex) Calculates the prior marginal probabilities of the given node.- Specified by:
- calculatePriorMarginalsin interface- BayesUpdater
- Parameters:
- nodeIndex- node index
- Returns:
- P(node = value), where value is the value of the node in the Bayes net.
 
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calculateUpdatedMarginalspublic double[] calculateUpdatedMarginals(int nodeIndex) Calculates the updated marginal probabilities of the given node, given the evidence.- Specified by:
- calculateUpdatedMarginalsin interface- BayesUpdater
- 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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toStringPrints out the most recent marginal.
 
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