repicea.simulation

Class ModelParameterEstimates

java.lang.Object

repicea.stats.RandomVariable<D>

repicea.stats.estimates.Estimate<GaussianDistribution>

repicea.stats.estimates.GaussianEstimate

repicea.simulation.ModelParameterEstimates

All Implemented Interfaces:

java.io.Serializable, CentralMomentsGettable, CentralMomentsSettable

Direct Known Subclasses:

SASParameterEstimates

public class ModelParameterEstimates
extends GaussianEstimate

The ModelParameterEstimates is a wrapper for parameter estimates. It includes a common variance- covariance matrix for the parameter estimates.

See Also:

Serialized Form

Nested Class Summary

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

Estimate.EstimatorType

Field Summary

Fields

Modifier and Type	Field and Description
protected java.util.List<java.lang.Integer>	estimatedParameterIndices

Fields inherited from class repicea.stats.estimates.Estimate

estimatorType, rowIndex

Constructor Summary

Constructors

Constructor and Description
ModelParameterEstimates(Matrix mean, Matrix variance) Constructor.

Method Summary

Modifier and Type	Method and Description
Matrix	getRandomDeviate() This method returns a random deviate from this estimate.
java.util.List<java.lang.Integer>	getTrueParameterIndices() This method returns the indices of the parameters that were truly estimated.
protected void	setEstimatedParameterIndices()

Methods inherited from class repicea.stats.estimates.GaussianEstimate

getConfidenceIntervalBounds, getQuantileForProbability, setMean, setVariance

Methods inherited from class repicea.stats.estimates.Estimate

getDifferenceEstimate, getEstimatorType, getProductEstimate, getProductEstimate, getProductOfManyEstimates, 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

Field Detail

estimatedParameterIndices

protected final java.util.List<java.lang.Integer> estimatedParameterIndices

Constructor Detail

ModelParameterEstimates

public ModelParameterEstimates(Matrix mean,
                               Matrix variance)

Constructor.

Parameters:

mean - a vector that corresponds to the mean value

variance - a symmetric positive definite matrix

Method Detail

setEstimatedParameterIndices

protected void setEstimatedParameterIndices()

getTrueParameterIndices

public java.util.List<java.lang.Integer> getTrueParameterIndices()

This method returns the indices of the parameters that were truly estimated. In the case of a SAS implementation, some parameters may actually be fake..

Returns:

a List of Integer which is a copy of the original list to avoid modifications.

getRandomDeviate

public Matrix getRandomDeviate()

Description copied from class: Estimate

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

Overrides:

getRandomDeviate in class Estimate<GaussianDistribution>

Returns:

a deviate from the underlying distribution as a Matrix instance