Uses of Class
gov.sandia.cognition.statistics.distribution.MultivariateGaussian

Packages that use MultivariateGaussian

Package	Description
gov.sandia.cognition.learning.data.feature	Provides data feature extractors.
gov.sandia.cognition.learning.function.categorization	Provides functions that output a discrete set of categories.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.
gov.sandia.cognition.statistics.bayesian.conjugate	Provides Bayesian estimation routines based on conjugate prior distribution of parameters of specific conditional distributions.
gov.sandia.cognition.statistics.distribution	Provides statistical distributions.

Uses of MultivariateGaussian in gov.sandia.cognition.learning.data.feature

Fields in gov.sandia.cognition.learning.data.feature declared as MultivariateGaussian

Modifier and Type	Field and Description
protected MultivariateGaussian	MultivariateDecorrelator.gaussian The underlying Gaussian.

Methods in gov.sandia.cognition.learning.data.feature that return MultivariateGaussian

Modifier and Type	Method and Description
MultivariateGaussian	MultivariateDecorrelator.getGaussian() Gets the underlying multivariate Gaussian.

Methods in gov.sandia.cognition.learning.data.feature with parameters of type MultivariateGaussian

Modifier and Type	Method and Description
void	MultivariateDecorrelator.setGaussian(MultivariateGaussian gaussian) Sets the underlying multivariate Gaussian.

Constructors in gov.sandia.cognition.learning.data.feature with parameters of type MultivariateGaussian

Constructor and Description
MultivariateDecorrelator(MultivariateGaussian gaussian) Creates a new instance of MultivariateDecorrelator with the given multivariate Gaussian.

Uses of MultivariateGaussian in gov.sandia.cognition.learning.function.categorization

Methods in gov.sandia.cognition.learning.function.categorization that return MultivariateGaussian

Modifier and Type	Method and Description
MultivariateGaussian	AbstractConfidenceWeightedBinaryCategorizer.createWeightDistribution()
MultivariateGaussian	ConfidenceWeightedBinaryCategorizer.createWeightDistribution() Creates a multivariate Gaussian distribution that represents the distribution of weight vectors that the algorithm has learned.

Uses of MultivariateGaussian in gov.sandia.cognition.statistics.bayesian

Fields in gov.sandia.cognition.statistics.bayesian declared as MultivariateGaussian

Modifier and Type	Field and Description
protected MultivariateGaussian	BayesianLinearRegression.weightPrior Prior distribution of the weights, typically a zero-mean, diagonal-variance distribution.

Methods in gov.sandia.cognition.statistics.bayesian that return MultivariateGaussian

Modifier and Type	Method and Description
MultivariateGaussian	ExtendedKalmanFilter.createInitialLearnedObject()
MultivariateGaussian	KalmanFilter.createInitialLearnedObject()
MultivariateGaussian	BayesianLinearRegression.getWeightPrior() Getter for weightPrior
MultivariateGaussian	BayesianRobustLinearRegression.getWeightPrior() Getter for weightPrior
MultivariateGaussian	GaussianProcessRegression.learn(java.util.Collection<? extends InputOutputPair<? extends InputType,java.lang.Double>> data)

Methods in gov.sandia.cognition.statistics.bayesian with parameters of type MultivariateGaussian

Modifier and Type	Method and Description
void	AbstractKalmanFilter.computeMeasurementBelief(MultivariateGaussian belief, Vector innovation, Matrix C) Updates the measurement belief by computing the Kalman gain and incorporating the innovation into the estimate
void	BayesianLinearRegression.IncrementalEstimator.SufficientStatistic.create(MultivariateGaussian distribution)
BayesianLinearRegression.PredictiveDistribution	BayesianLinearRegression.createPredictiveDistribution(MultivariateGaussian posterior) Creates the predictive distribution of outputs given the weight posterior
GaussianProcessRegression.PredictiveDistribution	GaussianProcessRegression.createPredictiveDistribution(MultivariateGaussian posterior, java.util.ArrayList<InputType> inputs) Creates the predictive distribution for future points.
abstract void	AbstractKalmanFilter.measure(MultivariateGaussian belief, Vector observation) Integrates a measurement into the system, refining the current belief of the state of the system
void	ExtendedKalmanFilter.measure(MultivariateGaussian belief, Vector observation)
void	KalmanFilter.measure(MultivariateGaussian belief, Vector observation)
abstract void	AbstractKalmanFilter.predict(MultivariateGaussian belief) Creates a prediction of the system's next state given the current belief state
void	ExtendedKalmanFilter.predict(MultivariateGaussian belief)
void	KalmanFilter.predict(MultivariateGaussian belief)
void	BayesianLinearRegression.setWeightPrior(MultivariateGaussian weightPrior) Setter for weightPrior
void	BayesianRobustLinearRegression.setWeightPrior(MultivariateGaussian weightPrior) Setter for weightPrior
void	AbstractKalmanFilter.update(MultivariateGaussian belief, Vector observation)

Constructors in gov.sandia.cognition.statistics.bayesian with parameters of type MultivariateGaussian

Constructor and Description
BayesianLinearRegression(double outputVariance, MultivariateGaussian weightPrior) Creates a new instance of BayesianLinearRegression
BayesianRobustLinearRegression(InverseGammaDistribution outputVariance, MultivariateGaussian weightPrior) Creates a new instance of BayesianRobustLinearRegression
IncrementalEstimator(double outputVariance, MultivariateGaussian weightPrior) Creates a new instance of IncrementalEstimator
IncrementalEstimator(InverseGammaDistribution outputVariance, MultivariateGaussian weightPrior) Creates a new instance of IncrementalEstimator
PredictiveDistribution(MultivariateGaussian posterior) Creates a new instance of PredictiveDistribution
PredictiveDistribution(MultivariateGaussian posterior, java.util.ArrayList<InputType> inputs) Creates a new instance of PredictiveDistribution
SufficientStatistic(MultivariateGaussian prior) Creates a new instance of SufficientStatistic

Uses of MultivariateGaussian in gov.sandia.cognition.statistics.bayesian.conjugate

Methods in gov.sandia.cognition.statistics.bayesian.conjugate that return MultivariateGaussian

Modifier and Type	Method and Description
MultivariateGaussian	MultivariateGaussianMeanBayesianEstimator.createConditionalDistribution(Vector parameter)
MultivariateGaussian	MultivariateGaussianMeanBayesianEstimator.createPredictiveDistribution(MultivariateGaussian posterior)

Methods in gov.sandia.cognition.statistics.bayesian.conjugate with parameters of type MultivariateGaussian

Modifier and Type	Method and Description
double	MultivariateGaussianMeanBayesianEstimator.computeEquivalentSampleSize(MultivariateGaussian belief)
MultivariateGaussianMeanBayesianEstimator.Parameter	MultivariateGaussianMeanBayesianEstimator.createParameter(MultivariateGaussian conditional, MultivariateGaussian prior)
MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter	MultivariateGaussianMeanCovarianceBayesianEstimator.createParameter(MultivariateGaussian conditional, NormalInverseWishartDistribution prior)
MultivariateGaussian	MultivariateGaussianMeanBayesianEstimator.createPredictiveDistribution(MultivariateGaussian posterior)
void	MultivariateGaussianMeanBayesianEstimator.update(MultivariateGaussian target, java.lang.Iterable<? extends Vector> data)
void	MultivariateGaussianMeanBayesianEstimator.update(MultivariateGaussian updater, Vector data)

Constructors in gov.sandia.cognition.statistics.bayesian.conjugate with parameters of type MultivariateGaussian

Constructor and Description
MultivariateGaussianMeanBayesianEstimator(Matrix knownCovarianceInverse, MultivariateGaussian belief) Creates a new instance of MultivariateGaussianMeanBayesianEstimator
MultivariateGaussianMeanBayesianEstimator(MultivariateGaussian conditional, MultivariateGaussian prior) Creates a new instance of PoissonBayesianEstimator
MultivariateGaussianMeanCovarianceBayesianEstimator(MultivariateGaussian conditional, NormalInverseWishartDistribution prior) Creates a new instance
Parameter(MultivariateGaussian conditional, MultivariateGaussian prior) Creates a new instance
Parameter(MultivariateGaussian conditional, NormalInverseWishartDistribution prior) Creates a new instance

Constructor parameters in gov.sandia.cognition.statistics.bayesian.conjugate with type arguments of type MultivariateGaussian

Constructor and Description
MultivariateGaussianMeanBayesianEstimator(BayesianParameter<Vector,MultivariateGaussian,MultivariateGaussian> parameter) Creates a new instance
MultivariateGaussianMeanBayesianEstimator(BayesianParameter<Vector,MultivariateGaussian,MultivariateGaussian> parameter) Creates a new instance
MultivariateGaussianMeanCovarianceBayesianEstimator(BayesianParameter<Matrix,MultivariateGaussian,NormalInverseWishartDistribution> parameter) Creates a new instance

Uses of MultivariateGaussian in gov.sandia.cognition.statistics.distribution

Subclasses of MultivariateGaussian in gov.sandia.cognition.statistics.distribution

Modifier and Type	Class and Description
static class	MultivariateGaussian.PDF PDF of a multivariate Gaussian

Fields in gov.sandia.cognition.statistics.distribution declared as MultivariateGaussian

Modifier and Type	Field and Description
protected MultivariateGaussian	MultivariateGaussianInverseGammaDistribution.gaussian Gaussian component
protected MultivariateGaussian	NormalInverseWishartDistribution.gaussian Generates the mean, given the covariance from the inverseWishart.

Methods in gov.sandia.cognition.statistics.distribution that return MultivariateGaussian

Modifier and Type	Method and Description
MultivariateGaussian	MultivariateGaussian.clone()
MultivariateGaussian	MultivariateGaussian.convolve(MultivariateGaussian other) Convolves this Gaussian with the other Gaussian.
MultivariateGaussian	MultivariateGaussianInverseGammaDistribution.getGaussian() Getter for gaussian
MultivariateGaussian	NormalInverseWishartDistribution.getGaussian() Getter for gaussian.
MultivariateGaussian	MultivariateGaussian.plus(MultivariateGaussian other) Adds two MultivariateGaussian random variables together and returns the resulting MultivariateGaussian
MultivariateGaussian	MultivariateGaussian.scale(Matrix premultiplyMatrix) Scales the MultivariateGaussian by premultiplying by the given Matrix
MultivariateGaussian	MultivariateGaussian.times(MultivariateGaussian other) Multiplies this Gaussian with the other Gaussian.

Methods in gov.sandia.cognition.statistics.distribution with parameters of type MultivariateGaussian

Modifier and Type	Method and Description
MultivariateGaussian	MultivariateGaussian.convolve(MultivariateGaussian other) Convolves this Gaussian with the other Gaussian.
void	MultivariateGaussian.SufficientStatistic.create(MultivariateGaussian distribution)
void	MultivariateGaussian.SufficientStatisticCovarianceInverse.create(MultivariateGaussian distribution)
MultivariateGaussian	MultivariateGaussian.plus(MultivariateGaussian other) Adds two MultivariateGaussian random variables together and returns the resulting MultivariateGaussian
void	MultivariateGaussianInverseGammaDistribution.setGaussian(MultivariateGaussian gaussian) Setter for gaussian
void	NormalInverseWishartDistribution.setGaussian(MultivariateGaussian gaussian) Setter for gaussian
MultivariateGaussian	MultivariateGaussian.times(MultivariateGaussian other) Multiplies this Gaussian with the other Gaussian.

Constructors in gov.sandia.cognition.statistics.distribution with parameters of type MultivariateGaussian

Constructor and Description
MultivariateGaussian(MultivariateGaussian other) Creates a new instance of MultivariateGaussian.
MultivariateGaussianInverseGammaDistribution(MultivariateGaussian gaussian, InverseGammaDistribution inverseGamma) Creates a new instance of MultivariateGaussianInverseGammaDistribution
NormalInverseWishartDistribution(MultivariateGaussian gaussian, InverseWishartDistribution inverseWishart, double covarianceDivisor) Creates a new instance of NormalInverseWishartDistribution
PDF(MultivariateGaussian... distributions) Creates a new instance of MixtureOfGaussians
PDF(MultivariateGaussian other) Creates a new instance of MultivariateGaussian.
PDF(MultivariateGaussian gaussian, InverseWishartDistribution inverseWishart, double covarianceDivisor) Creates a new instance of NormalInverseWishartDistribution

Constructor parameters in gov.sandia.cognition.statistics.distribution with type arguments of type MultivariateGaussian

Constructor and Description
PDF(java.util.Collection<? extends MultivariateGaussian> distributions) Creates a new instance of MixtureOfGaussians
PDF(java.util.Collection<? extends MultivariateGaussian> distributions, double[] priorWeights) Creates a new instance of LinearMixtureModel