gov.sandia.cognition.statistics.bayesian
Interface MetropolisHastingsAlgorithm.Updater<ObservationType,ParameterType>

Type Parameters:
ObservationType - Type of observations handled by the MCMC algorithm.
ParameterType - Type of parameters to infer.
All Superinterfaces:
Cloneable, CloneableSerializable, Serializable
Enclosing class:
MetropolisHastingsAlgorithm<ObservationType,ParameterType>

public static interface MetropolisHastingsAlgorithm.Updater<ObservationType,ParameterType>
extends CloneableSerializable

Creates proposals for the MCMC steps.


Method Summary
 double computeLogLikelihood(ParameterType parameter, Iterable<? extends ObservationType> data)
          Computes the log likelihood of the data given the parameter
 ParameterType createInitialParameter()
          Creates the initial parameterization
 WeightedValue<ParameterType> makeProposal(ParameterType location)
          Makes a proposal update given the current parameter set
 
Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable
clone
 

Method Detail

createInitialParameter

ParameterType createInitialParameter()
Creates the initial parameterization

Returns:
Initial parameters

computeLogLikelihood

double computeLogLikelihood(ParameterType parameter,
                            Iterable<? extends ObservationType> data)
Computes the log likelihood of the data given the parameter

Parameters:
parameter - Parameter to consider
data - Data to consider
Returns:
log likelihood of the data given the parameter

makeProposal

WeightedValue<ParameterType> makeProposal(ParameterType location)
Makes a proposal update given the current parameter set

Parameters:
location - Location from which to make a proposal
Returns:
Location of the proposed sample, weighted by the "q" ratio.