gov.sandia.cognition.statistics.distribution
Class MultivariateGaussian.IncrementalEstimator

java.lang.Object
  extended by gov.sandia.cognition.util.AbstractCloneableSerializable
      extended by gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner<DataType,SufficientStatisticsType>
          extended by gov.sandia.cognition.statistics.AbstractIncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic>
              extended by gov.sandia.cognition.statistics.distribution.MultivariateGaussian.IncrementalEstimator
All Implemented Interfaces:
BatchAndIncrementalLearner<Vector,MultivariateGaussian.SufficientStatistic>, BatchLearner<Collection<? extends Vector>,MultivariateGaussian.SufficientStatistic>, IncrementalLearner<Vector,MultivariateGaussian.SufficientStatistic>, IncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic>, CloneableSerializable, Serializable, Cloneable
Enclosing class:
MultivariateGaussian

public static class MultivariateGaussian.IncrementalEstimator
extends AbstractIncrementalEstimator<Vector,MultivariateGaussian,MultivariateGaussian.SufficientStatistic>

The estimator that creates a MultivariateGaussian from a stream of values.

See Also:
Serialized Form

Field Summary
static double DEFAULT_COVARIANCE
          Default covariance, 1.0E-5.
 
Constructor Summary
MultivariateGaussian.IncrementalEstimator()
          Default constructor
MultivariateGaussian.IncrementalEstimator(double defaultCovariance)
          Creates a new instance of IncrementalEstimator
 
Method Summary
 MultivariateGaussian.SufficientStatistic createInitialLearnedObject()
          Creates a new initial learned object, before any data is given.
 double getDefaultCovariance()
          Getter for defaultCovariance
 void setDefaultCovariance(double defaultCovariance)
          Setter for defaultCovariance
 
Methods inherited from class gov.sandia.cognition.statistics.AbstractIncrementalEstimator
clone, update
 
Methods inherited from class gov.sandia.cognition.learning.algorithm.AbstractBatchAndIncrementalLearner
learn, learn, update
 
Methods inherited from class java.lang.Object
equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchAndIncrementalLearner
learn
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner
learn
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.IncrementalLearner
update
 

Field Detail

DEFAULT_COVARIANCE

public static final double DEFAULT_COVARIANCE
Default covariance, 1.0E-5.

See Also:
Constant Field Values
Constructor Detail

MultivariateGaussian.IncrementalEstimator

public MultivariateGaussian.IncrementalEstimator()
Default constructor


MultivariateGaussian.IncrementalEstimator

public MultivariateGaussian.IncrementalEstimator(double defaultCovariance)
Creates a new instance of IncrementalEstimator

Parameters:
defaultCovariance - Default covariance of the distribution
Method Detail

getDefaultCovariance

public double getDefaultCovariance()
Getter for defaultCovariance

Returns:
Default covariance of the distribution

setDefaultCovariance

public void setDefaultCovariance(double defaultCovariance)
Setter for defaultCovariance

Parameters:
defaultCovariance - Default covariance of the distribution

createInitialLearnedObject

public MultivariateGaussian.SufficientStatistic createInitialLearnedObject()
Description copied from interface: IncrementalLearner
Creates a new initial learned object, before any data is given.

Returns:
The initial learned object.