@PublicationReference(author="Wikipedia",title="Conjugate Prior",type=WebPage,year=2009,url="http://en.wikipedia.org/wiki/Conjugate_prior") @PublicationReference(author={"Byron J. Gajewski","Stephen D. Simon","Susan E. Carlson"},title="Predicting accrual in clinical trials with Bayesian posterior predictive distributions",type=Journal,year=2008,publication="Statistics in Medicine",notes="They derive the predictive posterior for an inverse gamma, but we\'re using a gamma, so we have to invert the scale parameter.") public class ExponentialBayesianEstimator extends AbstractConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,ExponentialDistribution,GammaDistribution> implements ConjugatePriorBayesianEstimatorPredictor<java.lang.Double,java.lang.Double,ExponentialDistribution,GammaDistribution>
| Modifier and Type | Class and Description |
|---|---|
static class |
ExponentialBayesianEstimator.Parameter
Bayesian parameter describing this conjugate relationship.
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parameter| Modifier | Constructor and Description |
|---|---|
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ExponentialBayesianEstimator()
Default constructor.
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protected |
ExponentialBayesianEstimator(BayesianParameter<java.lang.Double,ExponentialDistribution,GammaDistribution> parameter)
Creates a new instance of ExponentialBayesianEstimator
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ExponentialBayesianEstimator(ExponentialDistribution conditional,
GammaDistribution prior)
Creates a new instance of ExponentialBayesianEstimator
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ExponentialBayesianEstimator(GammaDistribution prior)
Creates a new instance of ExponentialBayesianEstimator
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| Modifier and Type | Method and Description |
|---|---|
double |
computeEquivalentSampleSize(GammaDistribution belief)
Computes the equivalent sample size of using the given prior.
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ExponentialBayesianEstimator.Parameter |
createParameter(ExponentialDistribution conditional,
GammaDistribution prior)
Creates a parameter linking the conditional and prior distributions
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ParetoDistribution |
createPredictiveDistribution(GammaDistribution posterior)
Creates the predictive distribution of new data given the posterior.
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void |
update(GammaDistribution belief,
java.lang.Double data)
The
update method updates an object of ResultType using
the given new data of type DataType, using some form of
"learning" algorithm. |
clone, createConditionalDistribution, createInitialLearnedObject, getInitialBelief, getParameter, setParameterlearn, learn, updateequals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcreateConditionalDistribution, getParameterlearnclonecreateInitialLearnedObject, updatepublic ExponentialBayesianEstimator()
public ExponentialBayesianEstimator(GammaDistribution prior)
prior - Default conjugate prior.public ExponentialBayesianEstimator(ExponentialDistribution conditional, GammaDistribution prior)
prior - Default conjugate prior.conditional - Conditional distribution of the conjugate prior.protected ExponentialBayesianEstimator(BayesianParameter<java.lang.Double,ExponentialDistribution,GammaDistribution> parameter)
parameter - Bayesian parameter describing this conjugate relationship.public ExponentialBayesianEstimator.Parameter createParameter(ExponentialDistribution conditional, GammaDistribution prior)
ConjugatePriorBayesianEstimatorcreateParameter in interface ConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,ExponentialDistribution,GammaDistribution>conditional - Distribution from which observations are generatedprior - Distribution that generates parameters for the conditionalpublic void update(GammaDistribution belief, java.lang.Double data)
IncrementalLearnerupdate method updates an object of ResultType using
the given new data of type DataType, using some form of
"learning" algorithm.update in interface IncrementalLearner<java.lang.Double,GammaDistribution>belief - The object to update.data - The new data for the learning algorithm to use to update
the object.public double computeEquivalentSampleSize(GammaDistribution belief)
ConjugatePriorBayesianEstimatorcomputeEquivalentSampleSize in interface ConjugatePriorBayesianEstimator<java.lang.Double,java.lang.Double,ExponentialDistribution,GammaDistribution>belief - Prior belief to measure.public ParetoDistribution createPredictiveDistribution(GammaDistribution posterior)
BayesianEstimatorPredictorcreatePredictiveDistribution in interface BayesianEstimatorPredictor<java.lang.Double,java.lang.Double,GammaDistribution>posterior - Posterior distribution from which to compute the predictive posterior.