repicea.stats.estimates

Class JackknifeEstimate

java.lang.Object

repicea.stats.RandomVariable<D>

repicea.stats.estimates.Estimate<EmpiricalDistribution>

repicea.stats.estimates.JackknifeEstimate

All Implemented Interfaces:

java.io.Serializable, CentralMomentsGettable, NumberOfRealizationsProvider

public class JackknifeEstimate
extends Estimate<EmpiricalDistribution>

The JackknifeEstimate class implements the variance calculation typical of delete-d Jackknife variance estimator.

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class repicea.stats.estimates.Estimate

Estimate.EstimatorType

Field Summary

Fields inherited from class repicea.stats.estimates.Estimate

estimatorType, rowIndex

Constructor Summary

Constructors

Constructor and Description
JackknifeEstimate(int n, int d) Constructor.

Method Summary

Modifier and Type	Method and Description
void	addRealization(Matrix value) This method adds a realization to the empirical distribution.
ConfidenceInterval	getConfidenceIntervalBounds(double oneMinusAlpha) This method returns the probability of getting a lower valueand upper bound of a confidence intervals at probability level 1 - alpha
int	getNumberOfRealizations() This method returns the number of realizations the estimate is based on
java.util.List<Matrix>	getRealizations() This method returns the list of realizations in the empirical distribution.
Matrix	getVariance() This method returns the second central moment, i.e.

Methods inherited from class repicea.stats.estimates.Estimate

getDifferenceEstimate, getEstimatorType, getProductEstimate, getProductEstimate, getProductOfManyEstimates, getRandomDeviate, getRowIndex, getSumEstimate, isMergeableEstimate, setRowIndex

Methods inherited from class repicea.stats.RandomVariable

getDistribution, getMean

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

JackknifeEstimate

public JackknifeEstimate(int n,
                         int d)

Constructor.

Parameters:

n - the number of observations in the original sample

d - the number of left-out observations

Method Detail

getVariance

public Matrix getVariance()

Description copied from interface: CentralMomentsGettable

This method returns the second central moment, i.e. the variance-covariance matrix, of the random variable.

Specified by:

getVariance in interface CentralMomentsGettable

Overrides:

getVariance in class RandomVariable<EmpiricalDistribution>

Returns:

a Number instance

getConfidenceIntervalBounds

public ConfidenceInterval getConfidenceIntervalBounds(double oneMinusAlpha)

Description copied from class: Estimate

This method returns the probability of getting a lower valueand upper bound of a confidence intervals at probability level 1 - alpha

Specified by:

getConfidenceIntervalBounds in class Estimate<EmpiricalDistribution>

Parameters:

oneMinusAlpha - is 1 minus the probability of Type I error

Returns:

a ConfidenceInterval instance

addRealization

public void addRealization(Matrix value)

This method adds a realization to the empirical distribution. The conformity of the new realization is checked before adding it.

Parameters:

value - a Matrix

getRealizations

public java.util.List<Matrix> getRealizations()

This method returns the list of realizations in the empirical distribution.

Returns:

a List of Matrix instance

getNumberOfRealizations

public int getNumberOfRealizations()

Description copied from interface: NumberOfRealizationsProvider

This method returns the number of realizations the estimate is based on

Specified by:

getNumberOfRealizations in interface NumberOfRealizationsProvider

Returns:

an integer