Package | Description |
---|---|
com.bayesserver | |
com.bayesserver.analysis | |
com.bayesserver.causal | |
com.bayesserver.inference | |
com.bayesserver.optimization |
Modifier and Type | Method and Description |
---|---|
State |
State.copy()
Copies this instance.
|
State |
StateCollection.findByValue(Object value)
Finds the state whose
value /> matches the given [value], or null if a match is not found. |
State |
Variable.findStateByValue(Object value)
Finds a state based on a state value.
|
State |
StateCollection.get(int index)
Gets the
State at the specified index. |
State |
StateCollection.get(String name)
Performs a case sensitive lookup.
|
State |
StateCollection.get(String name,
boolean throwIfNotFound)
Performs a case sensitive lookup.
|
State |
StateContext.getState()
Gets the State.
|
State |
StateCollection.remove(int index)
Removes an element from the collection at the specified index.
|
State |
StateCollection.set(int index,
State value)
Sets the
State at the specified index. |
Modifier and Type | Method and Description |
---|---|
void |
StateCollection.add(int index,
State item)
Inserts an element into the collection at the specified index.
|
double |
Table.get(State... states)
Gets the table value corresponding to the given states.
|
double |
CLGaussian.getCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
State... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
CLGaussian.getCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
State... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
CLGaussian.getCovariance(Variable continuousHeadA,
Variable continuousHeadB,
State... discrete)
Gets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
double |
CLGaussian.getMean(VariableContext continuousHead,
State... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
CLGaussian.getMean(Variable continuousHead,
Integer time,
State... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
double |
CLGaussian.getMean(Variable continuousHead,
State... discrete)
Gets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
int |
Table.getSortedIndex(State... states)
Gets the index of the table element that corresponds to a particular combination of states.
|
double |
CLGaussian.getVariance(VariableContext continuousHead,
State... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
CLGaussian.getVariance(Variable continuousHead,
Integer time,
State... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
CLGaussian.getVariance(Variable continuousHead,
State... discrete)
Gets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
double |
CLGaussian.getWeight(VariableContext continuousHead,
VariableContext continuousTail,
State... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
CLGaussian.getWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
State... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
double |
CLGaussian.getWeight(Variable continuousHead,
Variable continuousTail,
State... discrete)
Gets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
Table.set(double value,
State... states)
Sets the table value corresponding to the given states.
|
State |
StateCollection.set(int index,
State value)
Sets the
State at the specified index. |
void |
CLGaussian.setCovariance(VariableContext continuousHeadA,
VariableContext continuousHeadB,
double value,
State... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
CLGaussian.setCovariance(Variable continuousHeadA,
Integer timeA,
Variable continuousHeadB,
Integer timeB,
double value,
State... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
CLGaussian.setCovariance(Variable continuousHeadA,
Variable continuousHeadB,
double value,
State... discrete)
Sets the covariance of the Gaussian distribution between [continuousHeadA] and [continuousHeadB] for a particular discrete combination (mixture).
|
void |
CLGaussian.setMean(VariableContext continuousHead,
double value,
State... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
CLGaussian.setMean(Variable continuousHead,
double value,
State... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
CLGaussian.setMean(Variable continuousHead,
Integer time,
double value,
State... discrete)
Sets the mean value of the Gaussian distribution for the specified [continuousHead] variable for the [discrete] combination.
|
void |
CLGaussian.setVariance(VariableContext continuousHead,
double value,
State... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
CLGaussian.setVariance(Variable continuousHead,
double value,
State... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
CLGaussian.setVariance(Variable continuousHead,
Integer time,
double value,
State... discrete)
Sets the variance of the Gaussian distribution for the specified [continuousHead] variable for a particular discrete combination (mixture).
|
void |
CLGaussian.setWeight(VariableContext continuousHead,
VariableContext continuousTail,
double value,
State... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
CLGaussian.setWeight(Variable continuousHead,
Integer timeHead,
Variable continuousTail,
Integer timeTail,
double value,
State... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
CLGaussian.setWeight(Variable continuousHead,
Variable continuousTail,
double value,
State... discrete)
Sets the weight/regression coefficient of the Gaussian distribution between the [continuousTail] and [continuousHead] for a particular discrete combination (mixture).
|
void |
NetworkMonitor.statesCollectionChange(Variable variable,
int index,
State add,
State remove,
CollectionAction action,
boolean complete)
For internal use.
|
Constructor and Description |
---|
Node(String name,
State... states)
|
StateContext(State state,
Integer time)
Initializes a new instance of
StateContext . |
Variable(String name,
State... states)
Initializes a new instance of the
Variable class, with VariableValueType discrete and the specified name and adds the states specified in [states]. |
Modifier and Type | Method and Description |
---|---|
State |
AutoInsightStateOutput.getState()
Gets the state this insight refers to.
|
State[] |
ParameterReference.getStates()
Gets the states which together locate a specific parameter in the node's distribution.
|
State |
AutoInsightOutput.getTarget()
Gets the target state used to calculate the insight.
|
Modifier and Type | Method and Description |
---|---|
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 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 double[][] |
Correlation.fromCovariance(CLGaussian gaussian,
State... states) |
SensitivityFunctionOneWay |
SensitivityToParameters.oneWay(Evidence evidence,
State hypothesis,
ParameterReference parameter)
Calculates how a hypothesis varies based on changes to a single parameter.
|
SensitivityFunctionTwoWay |
SensitivityToParameters.twoWay(Evidence evidence,
State hypothesis,
ParameterReference parameter1,
ParameterReference parameter2)
Calculates how a hypothesis varies based on changes to two parameters.
|
Constructor and Description |
---|
ParameterReference(Node node,
NodeDistributionKey key,
State[] states)
Initializes a new instance of the
ParameterReference class . |
ParameterReference(Node node,
State[] states)
Initializes a new instance of the
ParameterReference class. |
Modifier and Type | Method and Description |
---|---|
State |
EffectsAnalysisOutputItem.getTreatmentState()
Gets the treatment state used to measure the causal effect on the treatment.
|
Modifier and Type | Method and Description |
---|---|
void |
DefaultEvidence.setState(State state)
Sets evidence on a discrete state (hard evidence).
|
void |
Evidence.setState(State state)
Sets evidence on a discrete state (hard evidence).
|
void |
DefaultEvidence.setState(State state,
Integer time)
Sets evidence on a discrete state (hard evidence) at a particular time (zero based).
|
void |
Evidence.setState(State state,
Integer time)
Sets evidence on a discrete state (hard evidence) at a particular time (zero based).
|
void |
DefaultEvidence.setState(State state,
Integer time,
InterventionType interventionType)
Sets evidence on a discrete state (hard evidence), in the form of an intervention (do-operator).
|
void |
Evidence.setState(State state,
Integer time,
InterventionType interventionType)
Sets evidence on a discrete state (hard evidence), in the form of an intervention (do-operator).
|
Modifier and Type | Method and Description |
---|---|
State |
DesignState.getState()
Gets the state these options refer to.
|
State |
Objective.getState()
Gets the state being optimized.
|
Constructor and Description |
---|
DesignState(State state,
Double lowerBound,
Double upperBound)
Initializes a new instance of the
com.bayesserver.optization.DesignState class. |
Objective(State state,
ObjectiveKind kind)
Initializes a new instance of the
com.bayesserver.optimization.objective. class. |
Objective(State state,
ObjectiveKind kind,
Double value)
Initializes a new instance of the
com.bayesserver.optimization.objective. class. |
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