repicea.simulation.stemtaper

Class AbstractStemTaperEstimate

java.lang.Object

repicea.stats.RandomVariable<D>

repicea.stats.estimates.Estimate<Distribution>

repicea.simulation.stemtaper.AbstractStemTaperEstimate

All Implemented Interfaces:

java.io.Serializable, CentralMomentsGettable, CentralMomentsSettable

public abstract class AbstractStemTaperEstimate
extends Estimate<Distribution>
implements CentralMomentsSettable

The StemTaperEstimate class extends the Estimate class. It handles MonteCarlo or maximum likelihood based estimates. likelihood based. The method getMean() and getVariance() are overriden in order to select which super methods apply. The StemTaperEstimate handles the volume integration.

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
AbstractStemTaperEstimate(java.util.List<java.lang.Double> computedHeights) Constructor.

Method Summary

Modifier and Type	Method and Description
java.util.List<java.lang.Double>	getCrossSectionHeights() This method returns the heights of the cross sections for which the square diameters were predicted.
protected abstract double	getScalingFactor()
protected abstract Matrix	getSquaredDiameters(Matrix predictedDiameters)
protected abstract Matrix	getVarianceOfSquaredDiameter(Matrix variancePredictedDiameters)
Estimate<?>	getVolumeEstimate() This method returns a volume estimate from the integrated taper all along the heights contained in the heights member.
Estimate<?>	getVolumeEstimate(StemTaperSegmentList segments) This method returns a volume estimate from the integrated taper all along the selected segments.
void	setMean(Matrix mean) This method sets the mean vector of the random variable.
void	setVariance(Matrix variance) This method sets the variance-covariance matrix of the random variable.

Methods inherited from class repicea.stats.estimates.Estimate

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

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

Constructor Detail

AbstractStemTaperEstimate

public AbstractStemTaperEstimate(java.util.List<java.lang.Double> computedHeights)

Constructor.

Parameters:

computedHeights - a List instance containing the heights (m) of the cross sections

Method Detail

getVolumeEstimate

public Estimate<?> getVolumeEstimate()

This method returns a volume estimate from the integrated taper all along the heights contained in the heights member.

Returns:

an Estimate instance

getVolumeEstimate

public Estimate<?> getVolumeEstimate(StemTaperSegmentList segments)

This method returns a volume estimate from the integrated taper all along the selected segments.

Parameters:

segments - a StemTaperSegmentList that represents the selected taper (can be null, in such case the integration is carried out all along the heights, by default)

Returns:

an Estimate instance

getCrossSectionHeights

public java.util.List<java.lang.Double> getCrossSectionHeights()

This method returns the heights of the cross sections for which the square diameters were predicted.

Returns:

a List of Double instances

getSquaredDiameters

protected abstract Matrix getSquaredDiameters(Matrix predictedDiameters)

getVarianceOfSquaredDiameter

protected abstract Matrix getVarianceOfSquaredDiameter(Matrix variancePredictedDiameters)

getScalingFactor

protected abstract double getScalingFactor()

setMean

public void setMean(Matrix mean)

Description copied from interface: CentralMomentsSettable

This method sets the mean vector of the random variable.

Specified by:

setMean in interface CentralMomentsSettable

Parameters:

mean - a Matrix instance

setVariance

public void setVariance(Matrix variance)

Description copied from interface: CentralMomentsSettable

This method sets the variance-covariance matrix of the random variable.

Specified by:

setVariance in interface CentralMomentsSettable

Parameters:

variance - a Matrix instance