ObservationType
- Type of observations to use.public static class RejectionSampling.ScalarEstimator<ObservationType>
extends java.lang.Object
Modifier and Type | Class and Description |
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class |
RejectionSampling.ScalarEstimator.MinimizerFunction
Minimization function that measures the difference between the
logarithm of the sampler function minus the logarithm of the
conjunctive distribution.
|
Constructor and Description |
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ScalarEstimator(BayesianParameter<java.lang.Double,? extends ProbabilityFunction<ObservationType>,? extends UnivariateProbabilityDensityFunction> conjunctive,
java.lang.Iterable<? extends ObservationType> data)
Creates a new instance of ScalarEstimator
|
Modifier and Type | Method and Description |
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double |
estimateScalarFactor(UnivariateProbabilityDensityFunction sampler)
Estimates the minimum scalar needed for the sampler distribution to
envelope the conjunctive distribution
|
double |
logConjunctive(java.lang.Double parameter)
Computes the logarithm of the conjunctive likelihood for the given
parameter
|
public ScalarEstimator(BayesianParameter<java.lang.Double,? extends ProbabilityFunction<ObservationType>,? extends UnivariateProbabilityDensityFunction> conjunctive, java.lang.Iterable<? extends ObservationType> data)
conjunctive
- Defines the parameter that connects the conditional and prior
distributions.data
- Data to considerpublic double logConjunctive(java.lang.Double parameter)
parameter
- Parameter to update.public double estimateScalarFactor(UnivariateProbabilityDensityFunction sampler)
sampler
- Distribution from which we sample and envelop the conjunctive
distribution.