repicea.stats.estimates

Class Estimate<D extends Distribution>

java.lang.Object

repicea.stats.RandomVariable<D>

repicea.stats.estimates.Estimate<D>

Type Parameters:

D - a Distribution derived instance which represents the assumed distribution for the estimate

All Implemented Interfaces:

java.io.Serializable, CentralMomentsGettable

Direct Known Subclasses:

AbstractStemTaperEstimate, BootstrapHybridPointEstimate, GaussianErrorTermEstimate, GaussianEstimate, JackknifeEstimate, MonteCarloEstimate, PointEstimate, SimpleEstimate, TruncatedGaussianEstimate, UniformEstimate, VarianceEstimate

public abstract class Estimate<D extends Distribution>
extends RandomVariable<D>

The Estimate class is the basic class for all estimates.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	Estimate.EstimatorType The type of estimator.

Field Summary

Fields

Modifier and Type	Field and Description
protected Estimate.EstimatorType	estimatorType
protected java.util.List<java.lang.String>	rowIndex

Constructor Summary

Constructors

Modifier	Constructor and Description
protected	Estimate(D distribution)

Method Summary

Modifier and Type	Method and Description
abstract 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
Estimate<?>	getDifferenceEstimate(Estimate<?> estimate2) This method returns an difference estimate.
Estimate.EstimatorType	getEstimatorType() This method returns the type of the estimator.
Estimate<?>	getProductEstimate(double scalar) This method returns an difference estimate.
SimpleEstimate	getProductEstimate(Estimate<?> estimate) Returns an estimate of the product of two parametric univariate estimate.
static SimpleEstimate	getProductOfManyEstimates(java.util.List<Estimate> estimates)
Matrix	getRandomDeviate() This method returns a random deviate from this estimate.
java.util.List<java.lang.String>	getRowIndex() This method returns the row index.
Estimate<?>	getSumEstimate(Estimate<?> estimate2) This method returns a sum of two estimates.
protected boolean	isMergeableEstimate(Estimate<?> estimate) This method checks if the two point estimates are compatible.
void	setRowIndex(java.util.List<java.lang.String> rowIndex) This method makes it possible to set an optional row index.

Methods inherited from class repicea.stats.RandomVariable

getDistribution, getMean, getVariance

Methods inherited from class java.lang.Object

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

Field Detail

estimatorType

protected Estimate.EstimatorType estimatorType

rowIndex

protected java.util.List<java.lang.String> rowIndex

Constructor Detail

Estimate

protected Estimate(D distribution)

Method Detail

getEstimatorType

public Estimate.EstimatorType getEstimatorType()

This method returns the type of the estimator.

Returns:

an EstimatorType instance

setRowIndex

public void setRowIndex(java.util.List<java.lang.String> rowIndex)

This method makes it possible to set an optional row index. This is useful when the response is a vector.

Parameters:

rowIndex - a List of String instance

getRowIndex

public java.util.List<java.lang.String> getRowIndex()

This method returns the row index.

Returns:

a List of String instance or null if the row index has not been set.

getRandomDeviate

public Matrix getRandomDeviate()

This method returns a random deviate from this estimate. This method is useful for Monte Carlo simulations.

Returns:

a deviate from the underlying distribution as a Matrix instance

getDifferenceEstimate

public Estimate<?> getDifferenceEstimate(Estimate<?> estimate2)

This method returns an difference estimate.

Parameters:

estimate2 - an Estimate to be subtracted from this estimate.

Returns:

an Estimate

getSumEstimate

public Estimate<?> getSumEstimate(Estimate<?> estimate2)

This method returns a sum of two estimates.

Parameters:

estimate2 - an Estimate to be added to this estimate.

Returns:

an Estimate

getProductEstimate

public Estimate<?> getProductEstimate(double scalar)

This method returns an difference estimate.

Parameters:

scalar - a double to be multiplied by this estimate

Returns:

an Estimate

getConfidenceIntervalBounds

public abstract 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

Parameters:

oneMinusAlpha - is 1 minus the probability of Type I error

Returns:

a ConfidenceInterval instance

isMergeableEstimate

protected boolean isMergeableEstimate(Estimate<?> estimate)

This method checks if the two point estimates are compatible. The basic check consists of comparing the classes. Then, the matrix data is checked for consistency with previous data.

Parameters:

estimate -

Returns:

a boolean

getProductEstimate

public SimpleEstimate getProductEstimate(Estimate<?> estimate)

Returns an estimate of the product of two parametric univariate estimate. The variance estimator is based on Goodman's estimator.

Parameters:

estimate - an Estimate instance

Returns:

a SimpleEstimate instance

getProductOfManyEstimates

public static SimpleEstimate getProductOfManyEstimates(java.util.List<Estimate> estimates)