repicea.stats.estimates

Class GaussianEstimate

java.lang.Object

repicea.stats.RandomVariable<D>

repicea.stats.estimates.Estimate<GaussianDistribution>

repicea.stats.estimates.GaussianEstimate

All Implemented Interfaces:

java.io.Serializable, CentralMomentsGettable, CentralMomentsSettable

Direct Known Subclasses:

LinkedGaussianEstimate, ModelParameterEstimates

public class GaussianEstimate
extends Estimate<GaussianDistribution>
implements CentralMomentsSettable, java.io.Serializable

This class contains the elements related to the random effects, i.e. the best linear unbiased predictors (blups) as well as their variances.

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
GaussianEstimate() Common constructor.
GaussianEstimate(double mean, double variance) Constructor for univariate distribution.
GaussianEstimate(Matrix mean, Matrix variance) Constructor with the mean and variance.

Method Summary

Modifier and Type	Method and Description
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
protected Matrix	getQuantileForProbability(double probability)
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

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

GaussianEstimate

public GaussianEstimate()

Common constructor. By default the Gaussian distribution that supports this estimate has a mean 0 and a variance 1.

GaussianEstimate

public GaussianEstimate(Matrix mean,
                        Matrix variance)

Constructor with the mean and variance.

Parameters:

mean - a Matrix instance that contains the mean

variance - a Matrix that contains the variance

GaussianEstimate

public GaussianEstimate(double mean,
                        double variance)

Constructor for univariate distribution.

Parameters:

mean -

variance -

Method Detail

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

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

getQuantileForProbability

protected Matrix getQuantileForProbability(double probability)

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<GaussianDistribution>

Parameters:

oneMinusAlpha - is 1 minus the probability of Type I error

Returns:

a ConfidenceInterval instance