Uses of Class com.bayesserver.inference.InconsistentEvidenceException (bayesserver 11.0 API)

Packages that use InconsistentEvidenceException
Package	Description
com.bayesserver.analysis
com.bayesserver.causal
com.bayesserver.data.sampling
com.bayesserver.inference
com.bayesserver.learning.parameters

Uses of InconsistentEvidenceException in com.bayesserver.analysis

Methods in com.bayesserver.analysis that throw InconsistentEvidenceException
Modifier and Type	Method	Description
`static AssociationOutput`	Association.`calculate(List<AssociationPair> pairs, Evidence evidence, AssociationOptions options)`	Calculates the association/information between two sets of variables, such as those at either end of a Link.
`static AutoInsightOutput`	AutoInsight.`calculate(State target, List<Variable> testVariables, Evidence evidence, AutoInsightOptions options)`	Uses comparison queries to automatically derive insight about a target variable from a trained network.
`static AutoInsightOutput`	AutoInsight.`calculate(State target, List<Variable> testVariables, InferenceFactory factory)`	Uses comparison queries to automatically derive insight about a target variable from a trained network.
`static AutoInsightOutput`	AutoInsight.`calculate(State target, List<Variable> testVariables, InferenceFactory factory, Evidence evidence)`	Uses comparison queries to automatically derive insight about a target variable from a trained network.
`static AutoInsightOutput[]`	AutoInsight.`calculate(Variable continuousTarget, List<Interval<Double>> targetIntervals, List<Variable> testVariables, Evidence evidence, AutoInsightOptions options)`	Uses comparison queries to automatically derive insight about a target variable from a trained network.
`static ImpactOutput`	Impact.`calculate(Network network, Distribution hypothesisQuery, Evidence evidence, List<Variable> evidenceToAnalyse, ImpactOptions options)`	Analyzes the impact of sets of evidence on the resulting probability distribution of a hypothesis variable.
`static ImpactOutput`	Impact.`calculate(Network network, Distribution hypothesisQuery, StateContext[] hypothesisCombination, Evidence evidence, List<Variable> evidenceToAnalyse, ImpactOptions options)`	Analyzes the impact of sets of evidence on a hypothesis query and discrete combination of that hypothesis query.
`static ImpactOutput`	Impact.`calculate(Network network, Variable hypothesisVariable, Evidence evidence, List<Variable> evidenceToAnalyse, ImpactOptions options)`	Analyzes the impact of sets of evidence on a hypothesis state and its variable.
`static ImpactOutput`	Impact.`calculate(Network network, Variable hypothesisVariable, State hypothesisState, Evidence evidence, List<Variable> evidenceToAnalyse, ImpactOptions options)`	Analyzes the impact of sets of evidence on a hypothesis state and its variable.
`static LogLikelihoodAnalysisOutput`	LogLikelihoodAnalysis.`calculate(Network network, Evidence evidence, List<Variable> evidenceToAnalyse, LogLikelihoodAnalysisOptions options)`	Analyzes the log-likelihood based on subsets of evidence.
`static ValueOfInformationOutput`	ValueOfInformation.`calculate(VariableContext hypothesis, List<VariableContext> testVariables, Evidence evidence, InferenceFactory factory, ValueOfInformationOptions options)`	Calculates value of information, which can be used to determine which variables are most likely to reduce the uncertainty of a particular variable.
`static ValueOfInformationOutput`	ValueOfInformation.`calculate(Variable hypothesis, List<Variable> testVariables, Evidence evidence, InferenceFactory factory, ValueOfInformationOptions options)`	Calculates value of information, which can be used to determine which variables are most likely to reduce the uncertainty of a particular variable.
`static ImpactHypothesisOutput`	Impact.`calculateStreamed(Network network, Distribution hypothesisQuery, Evidence evidence, List<Variable> evidenceToAnalyse, ImpactAction outputItem, ImpactOptions options)`	Analyzes the impact of sets of evidence on the resulting probability distribution of a hypothesis variable.
`static ImpactHypothesisOutput`	Impact.`calculateStreamed(Network network, Distribution hypothesisQuery, StateContext[] hypothesisState, Evidence evidence, List<Variable> evidenceToAnalyse, ImpactAction outputItem, ImpactOptions options)`	Analyzes the impact of sets of evidence on a hypothesis query and discrete combination of that hypothesis query.
`static LogLikelihoodAnalysisBaselineOutput`	LogLikelihoodAnalysis.`calculateStreamed(Network network, Evidence evidence, List<Variable> evidenceToAnalyse, LogLikelihoodAnalysisAction outputItem, LogLikelihoodAnalysisOptions options)`	Analyzes the log-likelihood based on subsets of evidence.

Uses of InconsistentEvidenceException in com.bayesserver.causal

Methods in com.bayesserver.causal that throw InconsistentEvidenceException
Modifier and Type	Method	Description
`static EffectsAnalysisOutput`	EffectsAnalysis.`calculate(Variable treatment, Variable outcome, CausalEffectKind effect, Evidence fixedEvidence, InferenceFactory factory, EffectsAnalysisOptions options)`	Calculate the causal effect on a target, varying for different treatment values.
`void`	CausalInferenceBase.`query(QueryOptions queryOptions, QueryOutput queryOutput)`	Calculates a number of distributions, e.g.
`protected void`	BackdoorInference.`queryDistributionsInner(QueryOptions queryOptions, QueryOutput queryOutput)`
`protected abstract void`	CausalInferenceBase.`queryDistributionsInner(QueryOptions queryOptions, QueryOutput queryOutput)`
`protected void`	DisjunctiveCauseInference.`queryDistributionsInner(QueryOptions queryOptions, QueryOutput queryOutput)`
`protected void`	FrontDoorInference.`queryDistributionsInner(QueryOptions queryOptions, QueryOutput queryOutput)`
`static void`	Abduction.`update(Evidence evidence, List<Variable> abductionEvidenceVariables, List<Variable> characteristicVariables, AbductionOptions options)`	Performs abduction which is one of the steps in 'counterfactual analysis'.

Uses of InconsistentEvidenceException in com.bayesserver.data.sampling

Methods in com.bayesserver.data.sampling that throw InconsistentEvidenceException
Modifier and Type	Method	Description
`void`	DataSampler.`takeSample(Evidence sampleData, RandomNumberGenerator random, DataSamplingOptions options)`	Generates sample data from the Bayesian network or Dynamic Bayesian network.

Uses of InconsistentEvidenceException in com.bayesserver.inference

Methods in com.bayesserver.inference that throw InconsistentEvidenceException
Modifier and Type	Method	Description
`void`	Inference.`query(QueryOptions queryOptions, QueryOutput queryOutput)`	Calculates a number of distributions, e.g.
`void`	LikelihoodSamplingInference.`query(QueryOptions queryOptions, QueryOutput queryOutput)`	Calculates a number of distributions, e.g.
`void`	LoopyBeliefInference.`query(QueryOptions queryOptions, QueryOutput queryOutput)`	Calculates a number of distributions, e.g.
`void`	RelevanceTreeInference.`query(QueryOptions queryOptions, QueryOutput queryOutput)`	Calculates a number of distributions, e.g.
`void`	VariableEliminationInference.`query(QueryOptions queryOptions, QueryOutput queryOutput)`	Calculates a number of distributions, e.g.

Uses of InconsistentEvidenceException in com.bayesserver.learning.parameters

Methods in com.bayesserver.learning.parameters that throw InconsistentEvidenceException
Modifier and Type	Method	Description
`void`	OnlineLearning.`adapt(Evidence evidence, OnlineLearningOptions options)`	Adapt the parameters of a Bayesian network using Bayesian statistics.